diff --git a/.gitignore b/.gitignore
index eaebe9c..1795503 100644
--- a/.gitignore
+++ b/.gitignore
@@ -3,3 +3,4 @@
 .ipynb_checkpoints
 docs/build/html
 *.swp
+*.lnk
diff --git a/notebooks/2015-08-29-developing-juliafem.ipynb b/notebooks/2015-08-29-developing-juliafem.ipynb
index f5314b4..27f8ee4 100644
--- a/notebooks/2015-08-29-developing-juliafem.ipynb
+++ b/notebooks/2015-08-29-developing-juliafem.ipynb
@@ -25,31 +25,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 39,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n"
-     ]
-    },
     {
      "data": {
       "text/plain": [
-       "Logger(root,DEBUG,PipeEndpoint(open, 0 bytes waiting),root)"
+       "Logger(root,DEBUG,Base.PipeEndpoint(open, 0 bytes waiting),root)"
       ]
      },
-     "execution_count": 1,
+     "execution_count": 39,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -78,7 +65,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 40,
    "metadata": {
     "collapsed": false
    },
@@ -96,7 +83,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 41,
    "metadata": {
     "collapsed": false
    },
@@ -118,7 +105,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 42,
    "metadata": {
     "collapsed": false
    },
@@ -129,7 +116,7 @@
        "MyQuad4"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 42,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -160,7 +147,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 43,
    "metadata": {
     "collapsed": false
    },
@@ -171,7 +158,7 @@
        "get_element_dimension (generic function with 7 methods)"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 43,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -190,7 +177,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 44,
    "metadata": {
     "collapsed": false
    },
@@ -199,25 +186,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "09-Oct 01:41:19:INFO:root:Testing element MyQuad4\n",
-      "09-Oct 01:41:19:INFO:root:number of basis functions in this element: 4\n",
-      "09-Oct 01:41:19:INFO:root:Initializing element\n",
-      "09-Oct 01:41:19:INFO:root:Element dimension: 2\n",
-      "09-Oct 01:41:19:INFO:root:Creating new scalar field JuliaFEM.Field{Array{Int64,1}}(0.0,1,[1,2,3,4])\n",
-      "09-Oct 01:41:19:INFO:root:Pushing field to element.\n",
-      "09-Oct 01:41:19:INFO:root:Interpolating scalar field at [0.0,0.0]\n",
-      "09-Oct 01:41:19:INFO:root:Value: 2.5\n"
+      "20-loka 15:49:17:INFO:root:Testing element MyQuad4\n"
      ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "PipeEndpoint(open, 0 bytes waiting)"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -234,7 +204,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 45,
    "metadata": {
     "collapsed": false
    },
@@ -242,39 +212,41 @@
     {
      "data": {
       "text/plain": [
-       "2-element Array{JuliaFEM.Field{T},1}:\n",
-       " JuliaFEM.Field{Int64}(0.0,1,2)\n",
-       " JuliaFEM.Field{Int64}(1.0,1,3)"
+       "JuliaFEM.FieldSet(symbol(\"heat coefficient\"),JuliaFEM.Field[JuliaFEM.Field{Int64}(0.0,1,2),JuliaFEM.Field{Int64}(1.0,1,3)])"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 45,
      "metadata": {},
      "output_type": "execute_result"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "09-Oct 01:41:19:INFO:root:Element MyQuad4 passed tests.\n"
-     ]
     }
    ],
    "source": [
-    "using JuliaFEM: new_fieldset!, add_field!, interpolate, dinterpolate\n",
-    "el1 = MyQuad4([1, 2, 3, 4])\n",
-    "new_fieldset!(el1, \"temperature\")\n",
-    "add_field!(el1, \"temperature\", Field(0.0, [0.0, 0.0, 0.0, 0.0]))\n",
-    "add_field!(el1, \"temperature\", Field(1.0, [1.0, 2.0, 3.0, 4.0]))\n",
-    "new_fieldset!(el1, \"geometry\")\n",
-    "add_field!(el1, \"geometry\", Field(0.0, Vector[[0.0,0.0,0.0], [10.0,0.0,0.0], [10.0,1.0,0.0], [0.0,1.0,0.0]]))\n",
-    "new_fieldset!(el1, \"heat coefficient\")\n",
-    "add_field!(el1, \"heat coefficient\", Field(0.0, 2))\n",
-    "add_field!(el1, \"heat coefficient\", Field(1.0, 3))"
+    "using JuliaFEM: FieldSet, Field, interpolate, dinterpolate\n",
+    "element = MyQuad4([1, 2, 3, 4])\n",
+    "\n",
+    "geometry_field = Field(0.0, Vector[])  # Create empty field at time t=0.0\n",
+    "push!(geometry_field, [ 0.0, 0.0, 0.0])  # push some values for field\n",
+    "push!(geometry_field, [10.0, 0.0, 0.0])\n",
+    "push!(geometry_field, [10.0, 1.0, 0.0])\n",
+    "push!(geometry_field, [ 0.0, 1.0, 0.0])\n",
+    "geometry_fieldset = FieldSet(\"geometry\")  # create fieldset \"geometry\"\n",
+    "push!(geometry_fieldset, geometry_field)  # add field to fieldset\n",
+    "push!(element, geometry_fieldset) # add fieldset to element\n",
+    "\n",
+    "temperature_fieldset = FieldSet(\"temperature\")\n",
+    "push!(temperature_fieldset, Field(0.0, [0.0, 0.0, 0.0, 0.0]))\n",
+    "push!(temperature_fieldset, Field(1.0, [1.0, 2.0, 3.0, 4.0]))\n",
+    "push!(element, temperature_fieldset)\n",
+    "\n",
+    "heat_coefficient_fieldset = FieldSet(\"heat coefficient\")\n",
+    "push!(heat_coefficient_fieldset, Field(0.0, 2))\n",
+    "push!(heat_coefficient_fieldset, Field(1.0, 3))\n",
+    "push!(element, heat_coefficient_fieldset)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 46,
    "metadata": {
     "collapsed": false
    },
@@ -285,19 +257,19 @@
        "1.25"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 46,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# temperature at the middle poinf of the element, 1/4*(1+2+3+4) at t=0.5\n",
-    "interpolate(el1, \"temperature\", [0.0, 0.0], 0.5)"
+    "interpolate(element, \"temperature\", [0.0, 0.0], 0.5)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 47,
    "metadata": {
     "collapsed": false
    },
@@ -311,19 +283,19 @@
        " 0.0"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 47,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# geometry midpoint of element\n",
-    "interpolate(el1, \"geometry\", [0.0, 0.0], 0.0)"
+    "interpolate(element, \"geometry\", [0.0, 0.0], 0.0)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 48,
    "metadata": {
     "collapsed": false
    },
@@ -337,19 +309,19 @@
        " 0.0  0.0"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 48,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# interpolate derivatives works too\n",
-    "dinterpolate(el1, \"geometry\", [0.0, 0.0], 0.0)"
+    "dinterpolate(element, \"geometry\", [0.0, 0.0], 0.0)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 49,
    "metadata": {
     "collapsed": false
    },
@@ -360,19 +332,19 @@
        "2.5"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 49,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# interpolating scalar -> scalar.\n",
-    "interpolate(el1, \"heat coefficient\", [0.0, 0.0], 0.5)"
+    "interpolate(element, \"heat coefficient\", [0.0, 0.0], 0.5)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 50,
    "metadata": {
     "collapsed": false
    },
@@ -383,13 +355,13 @@
        "3"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 50,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "interpolate(el1, \"heat coefficient\", [0.0, 0.0], Inf)"
+    "interpolate(element, \"heat coefficient\", [0.0, 0.0], Inf)"
    ]
   },
   {
@@ -434,7 +406,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 51,
    "metadata": {
     "collapsed": false
    },
@@ -442,20 +414,21 @@
     {
      "data": {
       "text/plain": [
-       "get_unknown_field_name (generic function with 1 method)"
+       "get_unknown_field_name (generic function with 4 methods)"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 51,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "using JuliaFEM: Equation, IntegrationPoint, Quad4\n",
+    "using JuliaFEM: Equation, IntegrationPoint, Quad4, get_unknown_field_name\n",
     "\n",
     "abstract Heat <: Equation\n",
     "\n",
-    "get_unknown_field_name(eq::Heat) = symbol(\"temperature\")"
+    "# it's important to define for which fieldset to save unknown values when solving\n",
+    "JuliaFEM.get_unknown_field_name(eq::Heat) = symbol(\"temperature\")"
    ]
   },
   {
@@ -467,7 +440,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 52,
    "metadata": {
     "collapsed": false
    },
@@ -492,7 +465,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 53,
    "metadata": {
     "collapsed": false
    },
@@ -503,20 +476,20 @@
        "DC2D4"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 53,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "function DC2D4(el::Quad4)\n",
+    "function DC2D4(element::Quad4)\n",
     "    integration_points = [\n",
     "        IntegrationPoint(1.0/sqrt(3.0)*[-1, -1], 1.0),\n",
     "        IntegrationPoint(1.0/sqrt(3.0)*[ 1, -1], 1.0),\n",
     "        IntegrationPoint(1.0/sqrt(3.0)*[ 1,  1], 1.0),\n",
     "        IntegrationPoint(1.0/sqrt(3.0)*[-1,  1], 1.0)]\n",
-    "    new_fieldset!(el, \"temperature\") # assign new field \"temperature\" to element\n",
-    "    DC2D4(el, integration_points, [])\n",
+    "    push!(element, FieldSet(\"temperature\"))\n",
+    "    DC2D4(element, integration_points, [])\n",
     "end"
    ]
   },
@@ -529,7 +502,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 54,
    "metadata": {
     "collapsed": false
    },
@@ -537,10 +510,10 @@
     {
      "data": {
       "text/plain": [
-       "has_lhs (generic function with 2 methods)"
+       "has_lhs (generic function with 4 methods)"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 54,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -569,7 +542,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 55,
    "metadata": {
     "collapsed": false
    },
@@ -584,25 +557,28 @@
        " -1.0  -2.0  -1.0   4.0"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 55,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "using JuliaFEM: integrate, integrate_lhs, integrate_rhs, new_fieldset!, add_field!\n",
-    "el = Quad4([1, 2, 3, 4])\n",
-    "new_fieldset!(el, \"geometry\")\n",
-    "add_field!(el, \"geometry\", Field(0.0, Vector[[0.0,0.0], [1.0,0.0], [1.0,1.0], [0.0,1.0]]))\n",
-    "new_fieldset!(el, \"temperature thermal conductivity\")\n",
-    "add_field!(el, \"temperature thermal conductivity\", Field(0.0, 6.0))\n",
-    "eq = DC2D4(el)\n",
-    "integrate_lhs(eq, 1.0)"
+    "using JuliaFEM: integrate, integrate_lhs, integrate_rhs\n",
+    "element = Quad4([1, 2, 3, 4])\n",
+    "fieldset1 = FieldSet(\"geometry\")\n",
+    "field1 = Field(0.0, Vector[[0.0,0.0], [1.0,0.0], [1.0,1.0], [0.0,1.0]])\n",
+    "push!(fieldset1, field1)\n",
+    "fieldset2 = FieldSet(\"temperature thermal conductivity\")\n",
+    "push!(fieldset2, Field(0.0, 6.0))\n",
+    "push!(element, fieldset1)\n",
+    "push!(element, fieldset2)\n",
+    "equation = DC2D4(element)\n",
+    "integrate_lhs(equation, 1.0)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 56,
    "metadata": {
     "collapsed": false
    },
@@ -613,13 +589,13 @@
        "true"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 56,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "JuliaFEM.has_lhs(eq)"
+    "JuliaFEM.has_lhs(equation)"
    ]
   },
   {
@@ -631,7 +607,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 57,
    "metadata": {
     "collapsed": false
    },
@@ -642,13 +618,13 @@
        "true"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 57,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "isa(integrate_rhs(eq, 1.0), Void)"
+    "integrate_rhs(equation, 1.0) == nothing"
    ]
   },
   {
@@ -660,7 +636,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 58,
    "metadata": {
     "collapsed": false
    },
@@ -668,10 +644,10 @@
     {
      "data": {
       "text/plain": [
-       "has_rhs (generic function with 2 methods)"
+       "has_rhs (generic function with 4 methods)"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 58,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -688,11 +664,11 @@
     "    global_dofs :: Array{Int64, 1}\n",
     "end\n",
     "\n",
-    "function DC2D2(el::Seg2)\n",
+    "function DC2D2(element::Seg2)\n",
     "    integration_points = [\n",
-    "        IntegrationPoint([0], 2.0)]\n",
-    "    new_fieldset!(el, \"temperature\")\n",
-    "    DC2D2(el, integration_points, [])\n",
+    "        IntegrationPoint([0.0], 2.0)]\n",
+    "    push!(element, FieldSet(\"temperature\"))\n",
+    "    DC2D2(element, integration_points, [])\n",
     "end\n",
     "\n",
     "\"\"\"\n",
@@ -710,7 +686,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 59,
    "metadata": {
     "collapsed": false
    },
@@ -723,19 +699,17 @@
        " 50.0"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 59,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "el = Seg2([1, 2])\n",
-    "new_fieldset!(el, \"geometry\")\n",
-    "add_field!(el, \"geometry\", Field(0.0, Vector[[0.0,0.0], [0.0,1.0]]))\n",
-    "new_fieldset!(el, \"temperature flux\")\n",
-    "add_field!(el, \"temperature flux\", Field(0.0, 100.0))\n",
-    "eq = DC2D2(el)\n",
-    "integrate_rhs(eq, 1.0)"
+    "element = Seg2([1, 2])\n",
+    "push!(element, FieldSet(\"geometry\", [Field(0.0, Vector[[0.0,0.0], [0.0,1.0]])]))\n",
+    "push!(element, FieldSet(\"temperature flux\", [Field(0.0, 100.0)]))\n",
+    "equation = DC2D2(element)\n",
+    "integrate_rhs(equation, 1.0)"
    ]
   },
   {
@@ -749,7 +723,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 60,
    "metadata": {
     "collapsed": false
    },
@@ -760,7 +734,7 @@
        "PlaneHeatProblem"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 60,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -776,7 +750,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 61,
    "metadata": {
     "collapsed": false
    },
@@ -784,10 +758,10 @@
     {
      "data": {
       "text/plain": [
-       "get_equation (generic function with 3 methods)"
+       "get_equation (generic function with 6 methods)"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 61,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -807,7 +781,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 62,
    "metadata": {
     "collapsed": false
    },
@@ -816,14 +790,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "09-Oct 01:41:22:DEBUG:root:total dofs: 4\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "dofmap: Dict(4=>[3],2=>[1],3=>[2],5=>[4])\n"
+      "20-loka 15:49:17:DEBUG:root:total dofs: 4\n"
      ]
     },
     {
@@ -834,114 +801,40 @@
        "\t[2, 1]  =  300.0"
       ]
      },
-     "execution_count": 24,
+     "execution_count": 62,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "using JuliaFEM: get_connectivity, set_global_dofs!, get_global_dofs\n",
-    "using JuliaFEM: add_element!, get_equations, get_matrix_dimension\n",
+    "using JuliaFEM: add_element!, get_equations, get_matrix_dimension, calculate_global_dofs\n",
+    "using JuliaFEM: assign_global_dofs!, get_lhs, get_rhs\n",
     "\n",
     "# create elements and add necessary properties like connectivity and geometry\n",
     "el1 = Quad4([2, 3, 4, 5])\n",
-    "new_fieldset!(el1, \"geometry\")\n",
-    "add_field!(el1, \"geometry\", Field(0.0, Vector[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0]]))\n",
-    "new_fieldset!(el1, \"temperature thermal conductivity\")\n",
-    "add_field!(el1, \"temperature thermal conductivity\", Field(0.0, 6.0))\n",
+    "fs1geom = FieldSet(\"geometry\")\n",
+    "push!(fs1geom, Field(0.0, Vector[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0]]))\n",
+    "fs1temp = FieldSet(\"temperature thermal conductivity\")\n",
+    "push!(fs1temp, Field(0.0, 6.0))\n",
+    "push!(el1, fs1geom)\n",
+    "push!(el1, fs1temp)\n",
+    "\n",
     "el2 = Seg2([2, 3])\n",
-    "new_fieldset!(el2, \"geometry\")\n",
-    "add_field!(el2, \"geometry\", Field(0.0, Vector[[0.0, 0.0], [0.0, 1.0]]))\n",
-    "new_fieldset!(el2, \"temperature flux\")\n",
-    "add_field!(el2, \"temperature flux\", Field(1.0, 600.0))\n",
+    "fs2geom = FieldSet(\"geometry\")\n",
+    "push!(fs2geom, Field(0.0, Vector[[0.0, 0.0], [0.0, 1.0]]))\n",
+    "fs2temp = FieldSet(\"temperature flux\")\n",
+    "push!(fs2temp, Field(1.0, 600.0))\n",
+    "push!(el2, fs2geom)\n",
+    "push!(el2, fs2temp)\n",
     "\n",
     "problem = PlaneHeatProblem()\n",
-    "add_element!(problem, el1)\n",
-    "add_element!(problem, el2)\n",
-    "\n",
-    "function JuliaFEM.get_connectivity(pr::Problem)\n",
-    "    conn = Int[]\n",
-    "    for eq in get_equations(pr)\n",
-    "        el = get_element(eq)\n",
-    "        append!(conn, get_connectivity(el))\n",
-    "    end\n",
-    "    conn = unique(conn)\n",
-    "    return conn\n",
-    "end\n",
-    "\n",
-    "\"\"\"\n",
-    "Calculate global dofs for equations, maybe using some bandwidth\n",
-    "minimizing or fill reducing algorithm\n",
-    "\"\"\"\n",
-    "function calculate_global_dofs(pr::Problem)\n",
-    "    conn = get_connectivity(pr)\n",
-    "    dim = get_dimension(typeof(pr))\n",
-    "    ndofs = dim*length(conn)\n",
-    "    Logging.debug(\"total dofs: $ndofs\")\n",
-    "\n",
-    "    mconn = maximum(conn)\n",
-    "    gdofs = reshape(collect(1:mconn), dim, mconn)\n",
-    "    dofmap = Dict{Int64, Array{Int64, 1}}()\n",
-    "    for (i, c) in enumerate(conn)\n",
-    "        dofmap[c] = gdofs[:, i]\n",
-    "    end\n",
-    "    return dofmap\n",
-    "end\n",
-    "\n",
-    "\"\"\"\n",
-    "Assign global dofs for equations.\n",
-    "\"\"\"\n",
-    "function assign_global_dofs!(pr::Problem, dofmap)\n",
-    "    for eq in get_equations(pr)\n",
-    "        el = get_element(eq)\n",
-    "        c = get_connectivity(el)\n",
-    "        #gdofs = [dofmap[ci] for ci in c]\n",
-    "        gdofs = Int64[]\n",
-    "        for ci in c\n",
-    "            append!(gdofs, dofmap[ci])\n",
-    "        end\n",
-    "        set_global_dofs!(eq, gdofs)\n",
-    "    end\n",
-    "end\n",
+    "push!(problem, el1)\n",
+    "push!(problem, el2)\n",
     "\n",
     "dofmap = calculate_global_dofs(problem)\n",
-    "println(\"dofmap: $dofmap\")\n",
     "assign_global_dofs!(problem, dofmap)\n",
     "\n",
-    "function get_lhs(pr::Problem, t::Float64)\n",
-    "    I = Int64[]\n",
-    "    J = Int64[]\n",
-    "    V = Float64[]\n",
-    "    dim = get_dimension(typeof(pr))\n",
-    "    for eq in filter(has_lhs, get_equations(pr))\n",
-    "        dofs = get_global_dofs(eq)\n",
-    "        lhs = integrate_lhs(eq, t)\n",
-    "        for (li, i) in enumerate(dofs)\n",
-    "            for (lj, j) in enumerate(dofs)\n",
-    "                push!(I, i)\n",
-    "                push!(J, j)\n",
-    "                push!(V, lhs[li, lj])\n",
-    "            end\n",
-    "        end\n",
-    "    end\n",
-    "    return I, J, V\n",
-    "end\n",
-    "\n",
-    "function get_rhs(pr::Problem, t::Float64)\n",
-    "    I = Int64[]\n",
-    "    V = Float64[]\n",
-    "    dim = get_dimension(typeof(pr))\n",
-    "    for eq in filter(has_rhs, get_equations(pr))\n",
-    "        dofs = get_global_dofs(eq)\n",
-    "        rhs = integrate_rhs(eq, t)\n",
-    "        for (li, i) in enumerate(dofs)\n",
-    "            push!(I, i)\n",
-    "            push!(V, rhs[li])\n",
-    "        end\n",
-    "    end\n",
-    "    return I, V\n",
-    "end\n",
-    "\n",
     "t = 1.0\n",
     "A = sparse(get_lhs(problem, t)...)\n",
     "b = sparsevec(get_rhs(problem, t)..., size(A, 1))"
@@ -949,7 +842,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 63,
    "metadata": {
     "collapsed": false
    },
@@ -962,7 +855,7 @@
        "\t[2, 1]  =  100.0"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 63,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -984,7 +877,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 64,
    "metadata": {
     "collapsed": false
    },
@@ -992,118 +885,29 @@
     {
      "data": {
       "text/plain": [
-       "DirichletProblem"
+       "1-element Array{JuliaFEM.DirichletEquation,1}:\n",
+       " JuliaFEM.DBC2D2(JuliaFEM.Seg2([4,5],JuliaFEM.Basis(basis,j),Dict(symbol(\"reaction force\")=>JuliaFEM.FieldSet(symbol(\"reaction force\"),JuliaFEM.Field[]),:geometry=>JuliaFEM.FieldSet(:geometry,JuliaFEM.Field[JuliaFEM.Field{Array{Array{T,1},1}}(0.0,1,Array{T,1}[[0.0,0.0],[0.0,1.0]])]))),[JuliaFEM.IntegrationPoint([-0.5773502691896257],1.0,Dict{Any,Any}()),JuliaFEM.IntegrationPoint([0.5773502691896257],1.0,Dict{Any,Any}())],Int64[],fieldval)"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 64,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "abstract BoundaryProblem <: Problem\n",
+    "using JuliaFEM: DirichletProblem\n",
     "\n",
-    "type DirichletProblem <: BoundaryProblem\n",
-    "    equations :: Array{Equation, 1}\n",
-    "end\n",
-    "DirichletProblem() = DirichletProblem([])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "get_equation (generic function with 4 methods)"
-      ]
-     },
-     "execution_count": 27,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "abstract DirichletBC <: Equation\n",
-    "\n",
-    "get_unknown_field_name(eq::DirichletBC) = symbol(\"reaction force\")\n",
-    "\n",
-    "\"\"\"\n",
-    "Dirichlet boundary condition element for 2 node line segment\n",
-    "(plane problems).\n",
-    "\"\"\"\n",
-    "type DBC2D2 <: DirichletBC\n",
-    "    element :: Seg2\n",
-    "    integration_points :: Array{IntegrationPoint, 1}\n",
-    "    global_dofs :: Array{Int64, 1}\n",
-    "    fieldval :: Function\n",
-    "end\n",
-    "function DBC2D2(el::Seg2)\n",
-    "    integration_points = [\n",
-    "        IntegrationPoint([-sqrt(1/3)], 1.0),\n",
-    "        IntegrationPoint([+sqrt(1/3)], 1.0)]\n",
-    "    new_fieldset!(el, \"reaction force\")\n",
-    "    fieldval(X, t) = 0.0\n",
-    "    DBC2D2(el, integration_points, [], fieldval)\n",
-    "end\n",
-    "\n",
-    "function JuliaFEM.get_lhs(eq::DBC2D2, ip, t)\n",
-    "    el = get_element(eq)\n",
-    "    h = get_basis(el)(ip.xi)\n",
-    "    return h*h'\n",
-    "end\n",
-    "\n",
-    "function JuliaFEM.get_rhs(eq::DBC2D2, ip, t)\n",
-    "    el = get_element(eq)\n",
-    "    h = get_basis(el, ip.xi)\n",
-    "    f = eq.fieldval\n",
-    "    X = interpolate(el, \"geometry\", ip.xi, t)\n",
-    "    return h*f(X, t)\n",
-    "end\n",
-    "JuliaFEM.has_lhs(eq::DBC2D2) = true\n",
-    "JuliaFEM.has_rhs(eq::DBC2D2) = true\n",
-    "JuliaFEM.get_dimension(pr::Type{DirichletProblem}) = 1\n",
-    "JuliaFEM.get_equation(pr::Type{DirichletProblem}, el::Type{Seg2}) = DBC2D2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1-element Array{JuliaFEM.Equation,1}:\n",
-       " DBC2D2(JuliaFEM.Seg2([4,5],JuliaFEM.Basis(basis,j),Dict(symbol(\"reaction force\")=>JuliaFEM.Field[],:geometry=>JuliaFEM.Field[JuliaFEM.Field{Array{Array{T,1},1}}(0.0,1,Array{T,1}[[0.0,0.0],[0.0,1.0]])])),[JuliaFEM.IntegrationPoint([-0.5773502691896257],1.0,Dict{Any,Any}()),JuliaFEM.IntegrationPoint([0.5773502691896257],1.0,Dict{Any,Any}())],Int64[],fieldval)"
-      ]
-     },
-     "execution_count": 28,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
     "# create elements and add necessary properties like connectivity and geometry\n",
     "el3 = Seg2([4, 5])\n",
-    "new_fieldset!(el3, \"geometry\")\n",
-    "add_field!(el3, \"geometry\", Field(0.0, Vector[[0.0, 0.0], [0.0, 1.0]]))\n",
+    "push!(el3, FieldSet(\"geometry\", [Field(0.0, Vector[[0.0, 0.0], [0.0, 1.0]])]))\n",
     "\n",
     "bc1 = DirichletProblem()\n",
-    "#get_equation(typeof(bc1), typeof(el3))\n",
-    "#DBC2D2(el3)\n",
-    "add_element!(bc1, el3)"
+    "push!(bc1, el3)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 65,
    "metadata": {
     "collapsed": false
    },
@@ -1116,7 +920,7 @@
        "\t[4, 1]  =  0.0"
       ]
      },
-     "execution_count": 29,
+     "execution_count": 65,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1141,7 +945,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 66,
    "metadata": {
     "collapsed": false
    },
@@ -1156,7 +960,7 @@
        " -1.0  -2.0  -1.0   4.0"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 66,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1167,7 +971,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 67,
    "metadata": {
     "collapsed": false
    },
@@ -1182,7 +986,7 @@
        "   0.0"
       ]
      },
-     "execution_count": 31,
+     "execution_count": 67,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1193,7 +997,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 68,
    "metadata": {
     "collapsed": false
    },
@@ -1208,7 +1012,7 @@
        " 0.0  0.0  0.166667  0.333333"
       ]
      },
-     "execution_count": 32,
+     "execution_count": 68,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1219,7 +1023,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 69,
    "metadata": {
     "collapsed": false
    },
@@ -1234,7 +1038,7 @@
        " 0.0"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 69,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1245,7 +1049,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 70,
    "metadata": {
     "collapsed": false
    },
@@ -1278,7 +1082,7 @@
        "\t[4, 8]  =  0.333333"
       ]
      },
-     "execution_count": 34,
+     "execution_count": 70,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1289,7 +1093,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 71,
    "metadata": {
     "collapsed": false
    },
@@ -1304,7 +1108,7 @@
        "\t[8, 1]  =  0.0"
       ]
      },
-     "execution_count": 35,
+     "execution_count": 71,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1322,7 +1126,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 72,
    "metadata": {
     "collapsed": false
    },
@@ -1341,7 +1145,7 @@
        "  0.0   0.0   0.166667   0.333333  0.0  0.0  0.0       0.0     "
       ]
      },
-     "execution_count": 36,
+     "execution_count": 72,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1352,7 +1156,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 73,
    "metadata": {
     "collapsed": false
    },
@@ -1361,7 +1165,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Non-zero rows: [1,2,3,4,7,8]\n"
+      "Non-zero rows: [1,2,3,4,7,8]"
      ]
     },
     {
@@ -1378,7 +1182,7 @@
        " 600.0"
       ]
      },
-     "execution_count": 37,
+     "execution_count": 73,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1409,7 +1213,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 74,
    "metadata": {
     "collapsed": false
    },
@@ -1417,56 +1221,27 @@
     {
      "data": {
       "text/plain": [
-       "add_problem! (generic function with 1 method)"
+       "call (generic function with 1270 methods)"
       ]
      },
-     "execution_count": 38,
+     "execution_count": 74,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "abstract Solver\n",
+    "using JuliaFEM: Solver, get_problems\n",
     "\n",
-    "\"\"\"\n",
-    "Simple solver for educational purposes.\n",
-    "\"\"\"\n",
+    "\"\"\" Simple solver for educational purposes. \"\"\"\n",
     "type SimpleSolver <: Solver\n",
     "    problems\n",
     "end\n",
     "\n",
-    "\"\"\"\n",
-    "Default initializer\n",
-    "\"\"\"\n",
+    "\"\"\" Default initializer. \"\"\"\n",
     "function SimpleSolver()\n",
     "    SimpleSolver(Problem[])\n",
     "end\n",
     "\n",
-    "function add_problem!(solver::Solver, problem::Problem)\n",
-    "    push!(solver.problems, problem)\n",
-    "end"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "call (generic function with 1253 methods)"
-      ]
-     },
-     "execution_count": 39,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "get_problems(s::Solver) = s.problems\n",
     "\"\"\"\n",
     "Call solver to solve a set of problems.\n",
     "\n",
@@ -1516,7 +1291,7 @@
     "        element = get_element(equation)\n",
     "        field_name = get_unknown_field_name(equation)  # field we are solving\n",
     "        field = Field(t, full(x1[gdofs])[:])\n",
-    "        add_field!(element, field_name, field)\n",
+    "        push!(element[field_name], field)\n",
     "    end\n",
     "\n",
     "    # update field for elements in problem 2\n",
@@ -1525,7 +1300,7 @@
     "        element = get_element(equation)\n",
     "        field_name = get_unknown_field_name(equation)\n",
     "        field = Field(t, full(x2[gdofs]))\n",
-    "        add_field!(element, field_name, field)\n",
+    "        push!(element[field_name], field)\n",
     "    end\n",
     "end"
    ]
@@ -1541,41 +1316,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "5-element Array{Array{Float64,1},1}:\n",
-       " [-1.0,0.0]\n",
-       " [-0.5,0.5]\n",
-       " [0.0,1.0] \n",
-       " [0.5,1.5] \n",
-       " [1.0,2.0] "
-      ]
-     },
-     "execution_count": 40,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "\"\"\"\n",
-    "Simple linspace extension to multidimensional values.\n",
-    "\"\"\"\n",
-    "function Base.linspace(X1, X2, n)\n",
-    "    [1/2*(1-ti)*X1 + 1/2*(1+ti)*X2 for ti in linspace(-1, 1, n)]\n",
-    "end\n",
-    "\n",
-    "linspace([-1.0, 0.0], [1.0, 2.0], 5)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 75,
    "metadata": {
     "collapsed": false
    },
@@ -1584,59 +1325,45 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "09-Oct 01:41:25:DEBUG:root:total dofs: 4\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Residual norm: 9.845568954283847e-14\n",
-      "Array{T,1}[[0.0,0.0],[0.25,0.0],[0.5,0.0],[0.75,0.0],[1.0,0.0]]\n",
-      "[100.00000000000003,100.00000000000003,100.00000000000003,100.00000000000003,100.00000000000003]\n"
+      "20-loka 15:49:17:DEBUG:root:total dofs: 4\n"
      ]
     }
    ],
    "source": [
-    "using JuliaFEM: get_fieldset\n",
-    "\n",
     "# Define Problem 1:\n",
     "# - Field function: Laplace equation Δu=0 in Ω={u∈R²|(x,y)∈[0,1]×[0,1]}\n",
     "# - Neumann boundary on Γ₁={0<=x<=1, y=0}, ∂u/∂n=600 on Γ₁\n",
     "\n",
     "el1 = Quad4([1, 2, 3, 4])\n",
-    "new_fieldset!(el1, \"geometry\")\n",
-    "add_field!(el1, \"geometry\", Field(0.0, Vector[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0]]))\n",
-    "new_fieldset!(el1, \"temperature thermal conductivity\")\n",
-    "add_field!(el1, \"temperature thermal conductivity\", Field(0.0, 6.0))\n",
+    "push!(el1, FieldSet(\"geometry\", [Field(0.0, Vector[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0]])]))\n",
+    "push!(el1, FieldSet(\"temperature thermal conductivity\", [Field(0.0, 6.0)]))\n",
     "\n",
     "el2 = Seg2([1, 2])\n",
-    "new_fieldset!(el2, \"geometry\")\n",
-    "add_field!(el2, \"geometry\", Field(0.0, Vector[[0.0, 0.0], [1.0, 0.0]]))\n",
+    "push!(el2, FieldSet(\"geometry\", [Field(0.0, Vector[[0.0, 0.0], [1.0, 0.0]])]))\n",
     "\n",
     "# Boundary load, linear ramp 0 -> 600 at time 0 -> 1\n",
-    "new_fieldset!(el2, \"temperature flux\")\n",
-    "add_field!(el2, \"temperature flux\", Field(0.0, 0.0))\n",
-    "add_field!(el2, \"temperature flux\", Field(1.0, 600.0))\n",
+    "load = FieldSet(\"temperature flux\")\n",
+    "push!(load, Field(0.0, 0.0))\n",
+    "push!(load, Field(1.0, 600.0))\n",
+    "push!(el2, load)\n",
     "\n",
     "problem1 = PlaneHeatProblem()\n",
-    "add_element!(problem1, el1)\n",
-    "add_element!(problem1, el2)\n",
+    "push!(problem1, el1)\n",
+    "push!(problem1, el2)\n",
     "\n",
     "# Define Problem 2:\n",
     "# - Dirichlet boundary Γ₂={0<=x<=1, y=1}, u=0 on Γ₂\n",
     "\n",
     "el3 = Seg2([3, 4])\n",
-    "new_fieldset!(el3, \"geometry\")\n",
-    "add_field!(el3, \"geometry\", Field(0.0, Vector[[1.0, 1.0], [0.0, 1.0]]))\n",
+    "push!(el3, FieldSet(\"geometry\", [Field(0.0, Vector[[1.0, 1.0], [0.0, 1.0]])]))\n",
     "\n",
     "problem2 = DirichletProblem()\n",
-    "add_element!(problem2, el3)\n",
+    "push!(problem2, el3)\n",
     "\n",
     "# Create a solver for a set of problems\n",
     "solver = SimpleSolver()\n",
-    "add_problem!(solver, problem1)\n",
-    "add_problem!(solver, problem2)\n",
+    "push!(solver, problem1)\n",
+    "push!(solver, problem2)\n",
     "\n",
     "# Solve problem at time t=1.0 and update fields\n",
     "call(solver, 1.0)\n",
@@ -1650,6 +1377,41 @@
     "println(T)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Success :: (line:-1) :: fact was true\n",
+       "  Expression: mean(T) --> roughly(100.0)\n",
+       "    Expected: 100.0\n",
+       "    Occurred: 100.00000000000003"
+      ]
+     },
+     "execution_count": 76,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Residual norm: 9.845568954283847e-14\n",
+      "Array{T,1}[[0.0,0.0],[0.25,0.0],[0.5,0.0],[0.75,0.0],[1.0,0.0]]\n",
+      "[100.00000000000003,100.00000000000003,100.00000000000003,100.00000000000003,100.00000000000003]\n"
+     ]
+    }
+   ],
+   "source": [
+    "@fact mean(T) --> roughly(100.0)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -1668,20 +1430,11 @@
     "\n",
     "Any question about data structures, better ideas and improvements are very welcome."
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Julia 0.4.0-rc2",
+   "display_name": "Julia 0.4.0",
    "language": "julia",
    "name": "julia-0.4"
   },
diff --git a/notebooks/2015-09-15-2d-segmentation.ipynb b/notebooks/2015-09-15-2d-segmentation.ipynb
index 8bfe810..8c5f147 100644
--- a/notebooks/2015-09-15-2d-segmentation.ipynb
+++ b/notebooks/2015-09-15-2d-segmentation.ipynb
@@ -8,7 +8,7 @@
     "\n",
     "Author(s): Jukka Aho\n",
     "\n",
-    "**Abstract**: Contact segmentation in 2d"
+    "**Abstract**: Calculate mortar projection for 2d"
    ]
   },
   {
@@ -17,19 +17,10 @@
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "WARNING: could not import Base.help into PyCall\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "using JuliaFEM: PSeg, get_field, set_field, interpolate, new_field!, push_field!\n",
-    "using JuliaFEM: calculate_normals!, average_normals!, fit_derivative_field!\n",
-    "using JuliaFEM: set_degree, get_number_of_basis_functions, dinterpolate\n",
+    "using JuliaFEM: new_fieldset!, add_field!, dinterpolate\n",
+    "using JuliaFEM: Field, FieldSet, Seg2\n",
     "using PyPlot\n",
     "using ForwardDiff"
    ]
@@ -38,12 +29,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Create some test boundaries"
+    "Create some test boundaries:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 4,
    "metadata": {
     "collapsed": false
    },
@@ -54,7 +45,7 @@
        "rlinspace (generic function with 1 method)"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -90,7 +81,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1-element Array{Array{T,1},1}:\n",
+       " [0,1]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f = Field(0.0, Vector[])\n",
+    "push!(f.values, [0, 1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
@@ -99,35 +114,29 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Converged. p = [4.2905787641613236,5.624156522861784,0.04706336239279979,6.561746550428803]\n"
+      "Converged. p = [4.2905787641613236,5.624156522861784,0.04706336239279979,6.561746550428803]"
      ]
     },
     {
-     "data": {
-      "image/png": [
-       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"
-      ],
-      "text/plain": [
-       "PyPlot.Figure(PyObject <matplotlib.figure.Figure object at 0x7faeec09ee10>)"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "(-0.1,3.6)"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
+     "ename": "LoadError",
+     "evalue": "LoadError: \"Empty set of fields.\"\nwhile loading In[9], in expression starting on line 60",
+     "output_type": "error",
+     "traceback": [
+      "LoadError: \"Empty set of fields.\"\nwhile loading In[9], in expression starting on line 60",
+      "",
+      " in interpolate at C:\\Users\\jahx06\\.julia\\v0.4\\JuliaFEM\\src\\interpolate.jl:28",
+      " in dinterpolate at C:\\Users\\jahx06\\.julia\\v0.4\\JuliaFEM\\src\\elements.jl:208",
+      " in calculate_normals! at In[9]:36",
+      " in calculate_normals! at In[9]:33",
+      " [inlined code] from In[9]:61",
+      " in anonymous at no file:0"
+     ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "\n",
       "Converged. p = [2.110067133637596,1.2802355090457196,1.5675520985912952,-3.7904167887303712]\n"
      ]
     }
@@ -161,14 +170,30 @@
     "#x2 = linspace(0, 3, nm) + rand(nm)*0.1 + 0.4\n",
     "#y2 = 0.5*rand(nm) + 0.5\n",
     "\n",
+    "\"\"\"\n",
+    "Calculate element local normal field\n",
+    "\"\"\"\n",
+    "function calculate_normals!(el::Seg2, time, field_name=\"normal\")\n",
+    "    new_fieldset!(el, field_name)\n",
+    "    normal_field = Field(time, Vector[])\n",
+    "    for xi in Vector[[-1.0], [1.0]]\n",
+    "        tangent = dinterpolate(el, \"geometry\", xi, time)\n",
+    "        normal = [0 -1; 1 0]*tangent\n",
+    "        normal /= norm(normal)\n",
+    "        push!(normal_field.values, normal)\n",
+    "    end\n",
+    "    #add_field!(el, field_name, normal_field)\n",
+    "end\n",
+    "\n",
     "function create_elements(X, sid=0)\n",
     "    Γ = []\n",
     "    nnodes = size(X, 2)\n",
     "    nelements = nnodes-1\n",
     "    for i=1:nelements\n",
     "        con = sid+[i, i+1]\n",
-    "        el = PSeg(con)\n",
-    "        set_field(el, :Geometry, Vector[X[:, i], X[:, i+1]])\n",
+    "        el = Seg2(con)\n",
+    "        new_fieldset!(el, \"geometry\")\n",
+    "        #add_field!(el, \"geometry\", Field(0.0, Vector[X[:, i], X[:, i+1]]))\n",
     "        push!(Γ, el)\n",
     "    end\n",
     "    return Γ\n",
@@ -176,10 +201,70 @@
     "Γ₁ = create_elements([x1 y1]', 0)\n",
     "Γ₂ = create_elements([x2 y2]', nsl);\n",
     "\n",
-    "# calculate and average normals like se did in last notebook\n",
     "for el in [Γ₁; Γ₂]\n",
-    "    calculate_normals!(el)\n",
+    "    calculate_normals!(el, 0.0)\n",
     "end\n",
+    "\n",
+    "figure(figsize=(10, 3))\n",
+    "plot(x1, y1, \"-ko\")\n",
+    "plot(x2, y2, \"-ko\")\n",
+    "axis(\"equal\")\n",
+    "ylim(-0.1, 4.0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Calculating surface normals\n",
+    "\n",
+    "- must have unique normal"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Converged. p = [4.2905787641613236,5.624156522861784,0.04706336239279979,6.561746550428803]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "PyPlot.Figure(PyObject <matplotlib.figure.Figure object at 0x7faeec09ee10>)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(-0.1,3.6)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Converged. p = [2.110067133637596,1.2802355090457196,1.5675520985912952,-3.7904167887303712]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# calculate and average normals like we did in last notebook\n",
     "average_normals!(Γ₁)\n",
     "average_normals!(Γ₂)\n",
     "\n",
@@ -431,9 +516,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": [
-       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"
-      ],
+      "image/png": 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",
       "text/plain": [
        "PyPlot.Figure(PyObject <matplotlib.figure.Figure object at 0x7faed5beb5d0>)"
       ]
@@ -535,13 +618,15 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Julia 0.5.0-dev",
+   "display_name": "Julia 0.4.0",
    "language": "julia",
-   "name": "julia-0.5"
+   "name": "julia-0.4"
   },
   "language_info": {
+   "file_extension": ".jl",
+   "mimetype": "application/julia",
    "name": "julia",
-   "version": "0.5.0"
+   "version": "0.4.0"
   }
  },
  "nbformat": 4,
diff --git a/src/dirichlet.jl b/src/dirichlet.jl
index 5451760..35c36ae 100644
--- a/src/dirichlet.jl
+++ b/src/dirichlet.jl
@@ -27,13 +27,13 @@ type DBC2D2 <: DirichletEquation
     global_dofs :: Array{Int64, 1}
     fieldval :: Function
 end
-function DBC2D2(el::Seg2)
+function DBC2D2(element::Seg2)
     integration_points = [
         IntegrationPoint([-sqrt(1/3)], 1.0),
         IntegrationPoint([+sqrt(1/3)], 1.0)]
-    new_fieldset!(el, "reaction force")
+    push!(element, FieldSet("reaction force"))
     fieldval(X, t) = 0.0
-    DBC2D2(el, integration_points, [], fieldval)
+    DBC2D2(element, integration_points, [], fieldval)
 end
 function get_lhs(eq::DBC2D2, ip, t)
     el = get_element(eq)
diff --git a/src/elements.jl b/src/elements.jl
index d8a75b3..568bb0a 100644
--- a/src/elements.jl
+++ b/src/elements.jl
@@ -15,40 +15,25 @@ using ForwardDiff
 
 abstract Element
 
+""" Get FieldSet from element. """
+function Base.getindex(element::Element, field_name::Union{Symbol, ASCIIString})
+    element.fields[symbol(field_name)]
+end
+
+""" Add new FieldSet to element. """
+function Base.setindex!(element::Element, fieldset::FieldSet, fieldset_name::Union{Symbol, ASCIIString})
+    fieldset.name = symbol(fieldset_name)
+    element.fields[fieldset.name] = fieldset
+end
+function Base.push!(element::Element, fieldset::FieldSet)
+    element[fieldset.name] = fieldset
+end
+
+
 #= ELEMENT DEFINITIONS
 
-TODO: rewrite instructions after notebook.
-
-Each element must have
-
-1. Connectivity information. How element is connected to other elements.
-   This is typically node ids in Lagrange elements.
-2. Ability to store fields, in array of shape dim × nnodes, where dim is
-   dimension of field and nnodes is number of nodes of element. Note that
-   this is always 2d array.
-3. Default constructor which takes connectivity as argument.
-4. Basis functions and derivative of basis functions.
-
-These rules probably will change, but there's a test_element function which
-tests element and that it obeys current rules. If test_element passes,
-everything should be ok. I use Quad4 as an example element here.
-Several functions are inherited from Element abstract type:
-
-- get_connectivity
-- get_number_of_basis_functions*
-- get_element_dimension *
-- get_basis *
-- get_dbasisdxi *
-- get_dbasisdX
-- get_field
-- set_field
-- interpolate
-- ...
-
-Which should work if element is defined following some rules. Functions marked with asterisk * are the ones which must necessarily to implement by your own.
-
-Start of example
-----------------
+Example
+-------
 
 This is example how to create new element. This is commented because I use code
 generation for simple elements like Lagrage elements. Feel free to use
@@ -94,12 +79,6 @@ End of example.
 get_number_of_basis_functions(el::Type{Element}) = nothing
 get_element_dimension(el::Type{Element}) = nothing
 
-### LAGRANGE ELEMENTS ###
-#include("lagrange.jl")
-
-### HIERARCHICAL P-ELEMENTS ###
-#include("hierarchical.jl")
-
 ### COMMON ELEMENT ROUTINES ###
 
 """
@@ -115,10 +94,10 @@ Raises
 ------
 This uses FactCheck and throws exceptions if element is not passing all tests.
 """
-function test_element(eltype)
-    Logging.info("Testing element $eltype")
-    local el
-    n = get_number_of_basis_functions(eltype)
+function test_element(element_type)
+    Logging.info("Testing element $element_type")
+    local element
+    n = get_number_of_basis_functions(element_type)
     Logging.info("number of basis functions in this element: $n")
     @fact n --> not(nothing) """
     Unable to determine number of nodes for $eltype define a function
@@ -127,7 +106,7 @@ function test_element(eltype)
 
     Logging.info("Initializing element")
     try
-        el = eltype(collect(1:n))
+        element = element_type(collect(1:n))
     catch
         Logging.error("""
         Unable to create element with default constructor define function
@@ -135,31 +114,31 @@ function test_element(eltype)
         return false
     end
 
-    dim = get_element_dimension(eltype)
+    dim = get_element_dimension(element_type)
     Logging.info("Element dimension: $dim")
     @fact dim --> not(nothing) """
     Unable to get element dimension define function 'get_element_dimension'
     which return the dimension of this element (1, 2, 3)"""
 
     # try to interpolate some scalar field
-    fld = Field(0.0, collect(1:n))
-    Logging.info("Creating new scalar field $fld")
-    Logging.info("Pushing field to element.")
-    new_fieldset!(el, "field1")
-    add_field!(el, "field1", fld)
-    fieldset = get_fieldset(el, "field1")
-    @fact fieldset[1] --> fld
+    field = Field(0.0, collect(1:n))
+    Logging.info("Creating new scalar field $field")
+    fieldset = FieldSet("field1")
+    push!(fieldset, field)
+    push!(element, fieldset)
+    @fact element["field1"][1] --> fld
 
+    # evaluate basis functions at middle point of element
     mid = zeros(dim)
     try
-        get_basis(el)(mid)
+        get_basis(element)(mid)
     catch
         Logging.error("""
         Unable to evaluate basis, define function 'get_basis' for
         this element.""")
     end
     try
-        get_dbasisdxi(el)(mid)
+        get_dbasisdxi(element)(mid)
     catch
         Logging.error("""
         Unable to evaluate partial derivatives of basis,
@@ -167,46 +146,36 @@ function test_element(eltype)
     end
 
     Logging.info("Interpolating scalar field at $mid")
-    #f(field, xi, t) = el(xi)*el[field](t)
-    #i = f(:field1, mid, 0.0)
-    i = interpolate(el, "field1", mid, 0.0)
+    i = interpolate(element, "field1", mid, 0.0)
     Logging.info("Value: $i")
-    Logging.info("Element $eltype passed tests.")
+    Logging.info("Element $element_type passed tests.")
 end
 
+
 get_connectivity(el::Element) = el.connectivity
 
-"""
-Get basis functions of element.
-"""
+""" Get basis functions of element. """
 get_basis(el::Element) = el.basis
 get_basis(el::Element, xi::Vector) = el.basis(xi)
 Base.call(el::Element, xi::Vector) = el.basis(xi)
 
-"""
-Get partial derivatives of basis functions of element.
-"""
+""" Get partial derivatives of basis functions of element. """
 get_dbasisdxi(el::Element) = el.basis.dbasisdxi
 get_dbasisdxi(el::Element, xi::Vector) = el.basis.dbasisdxi(xi)
 
-"""
-Interpolate field on element.
-"""
-function interpolate(el::Element, field_name::Union{Symbol, ASCIIString}, xi::Vector, t::Number)
-    fieldset = get_fieldset(el, symbol(field_name))
-    field = interpolate(fieldset, t)
-    basis = get_basis(el)
+""" Interpolate field on element. """
+function interpolate(element::Element, field_name::Union{Symbol, ASCIIString}, xi::Vector, time::Number)
+    fieldset = element[field_name]
+    field = interpolate(fieldset, time)
+    basis = get_basis(element)
     interpolate(basis, field, xi)
 end
 
-"""
-Interpolate derivative of field on element.
-"""
-function dinterpolate(el::Element, field_name::Union{Symbol, ASCIIString}, xi::Vector, t::Number)
-    #get_dbasisdxi(el, xi)*el[field](t)
-    fieldset = get_fieldset(el, symbol(field_name))
-    field = interpolate(fieldset, t)
-    basis = get_basis(el)
+""" Interpolate derivative of field on element. """
+function dinterpolate(element::Element, field_name::Union{Symbol, ASCIIString}, xi::Vector, time::Number)
+    fieldset = element[field_name]
+    field = interpolate(fieldset, time)
+    basis = get_basis(element)
     dinterpolate(basis, field, xi)
 end
 
@@ -215,24 +184,24 @@ Get jacobian of element evaluated at point ξ on element in reference configurat
 
 Parameters
 ----------
-el :: Element
+element :: Element
 xi :: Vector
-geometry_field :: Any, optional
-time :: Number
+    spatial coordinate
+time :: Float64
+    temporal coordinate
+geometry_field :: optional
 
 Returns
 -------
 Vector or Matrix
-    depending on element type
+    depending on element dimension
 
 """
-function get_jacobian(el::Element, xi, t, geometry_field=symbol("geometry"))
-    dinterpolate(el, geometry_field, xi, t)
+function get_jacobian(element::Element, xi, time, geometry_field="geometry")
+    dinterpolate(element, geometry_field, xi, time)
 end
 
-"""
-Evaluate partial derivatives of basis, dbasis/dX
-"""
+""" Evaluate partial derivatives of basis, dbasis/dX, at some time t"""
 function get_dbasisdX(el::Element, xi, t)
     dbasisdxi = get_dbasisdxi(el, xi)
     J = get_jacobian(el, xi, t)
@@ -240,70 +209,8 @@ function get_dbasisdX(el::Element, xi, t)
 end
 
 
-""" Create new empty set of fields for element. """
-function new_fieldset!(el::Element, field_name::Union{Symbol, ASCIIString})
-    el.fields[symbol(field_name)] = FieldSet()
-end
-function new_fieldset!(el::Element, field_name::Union{Symbol, ASCIIString}, field::Field)
-    new_fieldset!(el, symbol(field_name))
-    add_field!(el, symbol(field_name), field)
-end
 
 
-""" Add new field to fieldset of element. """
-function add_field!(el::Element, field_name::Union{Symbol, ASCIIString}, field::Field)
-    push!(el.fields[symbol(field_name)], field)
-end
-
-
-""" Get fieldset. """
-function get_fieldset(el::Element, field_name::Union{Symbol, ASCIIString})
-    el.fields[symbol(field_name)]
-end
-""" Get fieldset, convenient function. """
-function Base.getindex(el::Element, field_name::Union{Symbol, ASCIIString})
-    get_fieldset(el, field_name)
-end
-
-
-
-
-"""
-calculate "local" normals in elements, in a way that
-n = Nᵢnᵢ gives some reasonable results for ξ ∈ [-1, 1]
-"""
-function calculate_normals!(el::Element, t, field_name=symbol("normals"))
-    new_field!(el, field_name, Vector)
-    for xi in Vector[[-1.0], [1.0]]
-        t = dinterpolate(el, :Geometry, xi)
-        n = [0 -1; 1 0]*t
-        n /= norm(n)
-        push_field!(el, field_name, n)
-    end
-end
-
-"""
-Alter normal field such that normals of adjacent elements are averaged.
-"""
-function average_normals!(elements, normal_field=symbol("normals"))
-    d = Dict()
-    for el in elements
-        c = get_connectivity(el)
-        n = get_field(el, normal_field)
-        for (ci, ni) in zip(c, n)
-            d[ci] = haskey(d, ci) ? d[ci] + ni : ni
-        end
-    end
-    for (ci, ni) in d
-        d[ci] /= norm(d[ci])
-    end
-    for el in elements
-        c = get_connectivity(el)
-        new_normals = [d[ci] for ci in c]
-        set_field(el, normal_field, new_normals)
-    end
-end
-
 
 # FIXME: These two needs integration -- maybe not in elements.jl ..?
 """
@@ -326,7 +233,7 @@ function fit_field!(el::Element, field, f, fixed_coeffs=Int[])
     xi = Vector[
         [0.0],
         [ 1/3*sqrt(5 - 2*sqrt(10/7))],
-        [-1/3*sqrt(5 - 2*sqrt(10/7))], 
+        [-1/3*sqrt(5 - 2*sqrt(10/7))],
         [ 1/3*sqrt(5 + 2*sqrt(10/7))],
         [-1/3*sqrt(5 + 2*sqrt(10/7))]]
     n = get_number_of_basis_functions(el)
@@ -390,7 +297,7 @@ function fit_derivative_field!(el::Element, field, f, fixed_coeffs=Int[])
     xi = Vector[
         [0.0],
         [ 1/3*sqrt(5 - 2*sqrt(10/7))],
-        [-1/3*sqrt(5 - 2*sqrt(10/7))], 
+        [-1/3*sqrt(5 - 2*sqrt(10/7))],
         [ 1/3*sqrt(5 + 2*sqrt(10/7))],
         [-1/3*sqrt(5 + 2*sqrt(10/7))]]
     n = get_number_of_basis_functions(el)
@@ -442,67 +349,3 @@ function fit_derivative_field!(el::Element, field, f, fixed_coeffs=Int[])
 end
 
 
-""" Find projection from slave nodes to master element. """
-function calc_projection_slave_nodes_to_master_element(sel, mel)
-    X1 = get_field(sel, :Geometry)
-    N1 = get_field(sel, :Normals)
-    X2(xi) = interpolate(mel, :Geometry, xi)
-    dX2(xi) = dinterpolate(mel, :Geometry, xi)
-    R(xi, k) = det([X2(xi) - X1[k] N1[k]]')
-    dR(xi, k) = det([dX2(xi) N1[k]]')
-    xi2 = Vector[[0.0], [0.0]]
-    for k=1:2
-        xi = xi2[k]
-        for i=1:3
-            dxi = -R(xi, k)/dR(xi, k)
-            xi += dxi
-            if abs(dxi) < 1.0e-9
-                break
-            end
-        end
-        xi2[k] = xi
-    end
-    clamp!(xi2, -1, 1)
-    return xi2
-end
-
-""" Find projection from master nodes to slave element. """
-function calc_projection_master_nodes_to_slave_element(sel, mel)
-    X1(xi) = interpolate(sel, :Geometry, xi)
-    dX1(xi) = dinterpolate(sel, :Geometry, xi)
-    N1(xi) = interpolate(sel, :Normals, xi)
-    dN1(xi) = dinterpolate(sel, :Normals, xi)
-    X2 = get_field(mel, :Geometry)
-    R(xi, k) = det([X1(xi) - X2[k] N1(xi)]')
-    dR(xi, k) = det([dX1(xi) N1(xi)]') + det([X1(xi) - X2[k] dN1(xi)]')
-    xi1 = Vector[[0.0], [0.0]]
-    for k=1:2
-        xi = xi1[k]
-        for i=1:3
-            dxi = -R(xi, k)/dR(xi, k)
-            xi += dxi
-            if abs(dxi) < 1.0e-9
-                break
-            end
-        end
-        xi1[k] = xi
-    end
-    clamp!(xi1, -1, 1)
-    return xi1
-end
-
-function has_projection(sel, mel)
-    xi1 = calc_projection_master_nodes_to_slave_element(sel, mel)
-    l = abs(xi1[2]-xi1[1])[1]
-    return l > 1.0e-9
-end
-
-"""
-Calculate projection between 1d boundary elements
-"""
-function calc_projection(sel, mel)
-    xi1 = calc_projection_master_nodes_to_slave_element(sel, mel)
-    xi2 = calc_projection_slave_nodes_to_master_element(sel, mel)
-    return xi1, xi2
-end
-
diff --git a/src/equations.jl b/src/equations.jl
index 7acd838..c454595 100644
--- a/src/equations.jl
+++ b/src/equations.jl
@@ -3,6 +3,11 @@
 
 abstract Equation
 
+function get_unknown_field_name(equation::Equation)
+    eqtype = typeof(equation)
+    error("define get_unknown_field_name for this equation type $eqtype")
+end
+
 """
 Integration point
 
diff --git a/src/heat.jl b/src/heat.jl
index c45dd49..1007d89 100644
--- a/src/heat.jl
+++ b/src/heat.jl
@@ -36,19 +36,19 @@ type DC2D4 <: HeatEquation
     integration_points :: Array{IntegrationPoint, 1}
     global_dofs :: Array{Int64, 1}
 end
-function DC2D4(el::Quad4)
+function DC2D4(element::Quad4)
     integration_points = [
         IntegrationPoint(1.0/sqrt(3.0)*[-1, -1], 1.0),
         IntegrationPoint(1.0/sqrt(3.0)*[ 1, -1], 1.0),
         IntegrationPoint(1.0/sqrt(3.0)*[ 1,  1], 1.0),
         IntegrationPoint(1.0/sqrt(3.0)*[-1,  1], 1.0)]
-    new_fieldset!(el, "temperature")
-    DC2D4(el, integration_points, [])
+    push!(element, FieldSet("temperature"))
+    DC2D4(element, integration_points, [])
 end
-function get_lhs(eq::DC2D4, ip, t)
-    el = get_element(eq)
-    dNdX = get_dbasisdX(el, ip.xi, t)
-    k = interpolate(el, "temperature thermal conductivity", ip.xi, t)
+function get_lhs(equation::DC2D4, ip, time)
+    element = get_element(equation)
+    dNdX = get_dbasisdX(element, ip.xi, time)
+    k = interpolate(element, "temperature thermal conductivity", ip.xi, time)
     return dNdX*k*dNdX'
 end
 JuliaFEM.has_lhs(eq::DC2D4) = true
@@ -59,17 +59,15 @@ type DC2D2 <: HeatEquation
     integration_points :: Array{IntegrationPoint, 1}
     global_dofs :: Array{Int64, 1}
 end
-function DC2D2(el::Seg2)
-    integration_points = [IntegrationPoint([0.0], 1.0)]
-    new_fieldset!(el, "temperature")
-    DC2D2(el, integration_points, [])
+function DC2D2(element::Seg2)
+    integration_points = [IntegrationPoint([0.0], 2.0)]
+    push!(element, FieldSet("temperature"))
+    DC2D2(element, integration_points, [])
 end
-function get_rhs(eq::DC2D2, ip, t)
-    el = get_element(eq)
-    h = get_basis(el, ip.xi)
-    f = interpolate(el, "temperature flux", ip.xi, t)
-    println("h = $h")
-    println("f = $f")
+function get_rhs(equation::DC2D2, ip, time)
+    element = get_element(equation)
+    h = get_basis(element, ip.xi)
+    f = interpolate(element, "temperature flux", ip.xi, time)
     return h*f
 end
 JuliaFEM.has_rhs(eq::DC2D2) = true
diff --git a/src/interpolate.jl b/src/interpolate.jl
index f4c66ee..3921dc5 100644
--- a/src/interpolate.jl
+++ b/src/interpolate.jl
@@ -31,7 +31,7 @@ function interpolate(fields::FieldSet, t::Number)
         return Field(t, fields[1].values)
     end
     if t >= fields[end].time
-        return fields[end]
+        return Field(t, fields[end].values)
     end
     i = length(fields)
     while fields[i].time >= t
diff --git a/src/lagrange.jl b/src/lagrange.jl
index 92901c4..754d9c9 100644
--- a/src/lagrange.jl
+++ b/src/lagrange.jl
@@ -36,14 +36,14 @@ macro create_lagrange_element(element_name, element_description, X, P)
         global get_number_of_basis_functions, get_element_dimension
         dim = size($X, 1)
         nbasis = size($X, 2)
-        h = calculate_lagrange_basis($P, $X)
+        basis = calculate_lagrange_basis($P, $X)
         type $eltype <: CG
             connectivity :: Array{Int, 1}
             basis :: Basis
-            fields :: Dict{Symbol, Array{Field, 1}}
+            fields :: Dict{Symbol, FieldSet}
         end
         function $eltype(connectivity, args...)
-            $eltype(connectivity, Basis(h), Dict())
+            $eltype(connectivity, Basis(basis), Dict())
         end
         get_element_description(el::Type{$eltype}) = $element_description
         get_number_of_basis_functions(el::Type{$eltype}) = nbasis
diff --git a/src/mortar.jl b/src/mortar.jl
new file mode 100644
index 0000000..e7e48f8
--- /dev/null
+++ b/src/mortar.jl
@@ -0,0 +1,101 @@
+"""
+calculate "local" normals in elements, in a way that
+n = Nᵢnᵢ gives some reasonable results for ξ ∈ [-1, 1]
+"""
+function calculate_normals!(el::Element, t, field_name=symbol("normals"))
+    new_field!(el, field_name, Vector)
+    for xi in Vector[[-1.0], [1.0]]
+        t = dinterpolate(el, :Geometry, xi)
+        n = [0 -1; 1 0]*t
+        n /= norm(n)
+        push_field!(el, field_name, n)
+    end
+end
+
+"""
+Alter normal field such that normals of adjacent elements are averaged.
+"""
+function average_normals!(elements, normal_field=symbol("normals"))
+    d = Dict()
+    for el in elements
+        c = get_connectivity(el)
+        n = get_field(el, normal_field)
+        for (ci, ni) in zip(c, n)
+            d[ci] = haskey(d, ci) ? d[ci] + ni : ni
+        end
+    end
+    for (ci, ni) in d
+        d[ci] /= norm(d[ci])
+    end
+    for el in elements
+        c = get_connectivity(el)
+        new_normals = [d[ci] for ci in c]
+        set_field(el, normal_field, new_normals)
+    end
+end
+
+
+""" Find projection from slave nodes to master element. """
+function calc_projection_slave_nodes_to_master_element(sel, mel)
+    X1 = get_field(sel, :Geometry)
+    N1 = get_field(sel, :Normals)
+    X2(xi) = interpolate(mel, :Geometry, xi)
+    dX2(xi) = dinterpolate(mel, :Geometry, xi)
+    R(xi, k) = det([X2(xi) - X1[k] N1[k]]')
+    dR(xi, k) = det([dX2(xi) N1[k]]')
+    xi2 = Vector[[0.0], [0.0]]
+    for k=1:2
+        xi = xi2[k]
+        for i=1:3
+            dxi = -R(xi, k)/dR(xi, k)
+            xi += dxi
+            if abs(dxi) < 1.0e-9
+                break
+            end
+        end
+        xi2[k] = xi
+    end
+    clamp!(xi2, -1, 1)
+    return xi2
+end
+
+""" Find projection from master nodes to slave element. """
+function calc_projection_master_nodes_to_slave_element(sel, mel)
+    X1(xi) = interpolate(sel, :Geometry, xi)
+    dX1(xi) = dinterpolate(sel, :Geometry, xi)
+    N1(xi) = interpolate(sel, :Normals, xi)
+    dN1(xi) = dinterpolate(sel, :Normals, xi)
+    X2 = get_field(mel, :Geometry)
+    R(xi, k) = det([X1(xi) - X2[k] N1(xi)]')
+    dR(xi, k) = det([dX1(xi) N1(xi)]') + det([X1(xi) - X2[k] dN1(xi)]')
+    xi1 = Vector[[0.0], [0.0]]
+    for k=1:2
+        xi = xi1[k]
+        for i=1:3
+            dxi = -R(xi, k)/dR(xi, k)
+            xi += dxi
+            if abs(dxi) < 1.0e-9
+                break
+            end
+        end
+        xi1[k] = xi
+    end
+    clamp!(xi1, -1, 1)
+    return xi1
+end
+
+function has_projection(sel, mel)
+    xi1 = calc_projection_master_nodes_to_slave_element(sel, mel)
+    l = abs(xi1[2]-xi1[1])[1]
+    return l > 1.0e-9
+end
+
+"""
+Calculate projection between 1d boundary elements
+"""
+function calc_projection(sel, mel)
+    xi1 = calc_projection_master_nodes_to_slave_element(sel, mel)
+    xi2 = calc_projection_slave_nodes_to_master_element(sel, mel)
+    return xi1, xi2
+end
+
diff --git a/src/problems.jl b/src/problems.jl
index b9426ca..0087934 100644
--- a/src/problems.jl
+++ b/src/problems.jl
@@ -22,6 +22,10 @@ function add_element!(problem::Problem, element::Element)
     equation = get_equation(typeof(problem), typeof(element))
     push!(problem.equations, equation(element))
 end
+function Base.push!(problem::Problem, element::Element)
+    equation = get_equation(typeof(problem), typeof(element))
+    push!(problem.equations, equation(element))
+end
 
 """
 Return total number of basis functions in problem
@@ -59,14 +63,15 @@ function set_global_dofs!(pr::Problem)
     end
 end
 
-function get_connectivity(pr::Problem)
-    conn = Int[]
-    for eq in get_equations(pr)
-        el = get_element(eq)
-        append!(conn, get_connectivity(el))
+""" Return unique list of connectivity (i.e. node ids). """
+function get_connectivity(problem::Problem)
+    connectivity = Int[]
+    for equation in get_equations(problem)
+        element = get_element(equation)
+        append!(connectivity, get_connectivity(element))
     end
-    conn = unique(conn)
-    return conn
+    connectivity = unique(connectivity)
+    return connectivity
 end
 
 """
diff --git a/src/solvers.jl b/src/solvers.jl
index daf11ef..58532b2 100644
--- a/src/solvers.jl
+++ b/src/solvers.jl
@@ -5,12 +5,13 @@
 
 abstract Solver
 
-"""
-Add new problem to solver
-"""
+""" Add new problem to solver. """
 function add_problem!(solver::Solver, problem::Problem)
     push!(solver.problems, problem)
 end
+function Base.push!(solver::Solver, problem::Problem)
+    push!(solver.problems, problem)
+end
 
 """
 Get all problems assigned to solver
@@ -53,12 +54,10 @@ function call(solver::SimpleSolver, t)
     # assemble problem 2
     A2 = sparse(get_lhs(problem2, t)...)
     b2 = sparsevec(get_rhs(problem2, t)..., size(A2, 1))
-    
+
     # make one monolithic assembly
     A = [A1 A2; A2' zeros(A2)]
     b = [b1; b2]
-    dump(full(A))
-    dump(full(b))
 
     # solve problem
     nz = unique(rowvals(A))
@@ -80,7 +79,7 @@ function call(solver::SimpleSolver, t)
         element = get_element(equation)
         field_name = get_unknown_field_name(equation)  # field we are solving
         field = Field(t, full(x1[gdofs])[:])
-        add_field!(element, field_name, field)
+        push!(element[field_name], field)
     end
 
     # update field for elements in problem 2
@@ -89,7 +88,7 @@ function call(solver::SimpleSolver, t)
         element = get_element(equation)
         field_name = get_unknown_field_name(equation)
         field = Field(t, full(x2[gdofs]))
-        add_field!(element, field_name, field)
+        push!(element[field_name], field)
     end
 end
 
diff --git a/src/types.jl b/src/types.jl
index dcd1f0d..747b448 100644
--- a/src/types.jl
+++ b/src/types.jl
@@ -5,7 +5,7 @@
 
 using ForwardDiff
 
-""" Field is a fundamental type which holds some values in some time t """
+""" Field is a fundamental data type which holds some values in some time t """
 type Field{T}
     time :: Float64
     increment :: Int64
@@ -19,6 +19,10 @@ end
 function Base.length(f::Field)
     length(f.values)
 end
+""" Push value to field. """
+function Base.push!(f::Field, value)
+    push!(f.values, value)
+end
 """ Get field discrete value at point i. """
 function Base.getindex(f::Field, i::Int64)
     f.values[i]
@@ -43,17 +47,39 @@ function Base.(:+)(f1::Field, f2::Field)
     Field(f1.time, f1.values + f2.values)
 end
 
-"""
-FieldSet is array of fields, each field maybe having different time and/or increment.
-"""
-typealias FieldSet Array{Field, 1}
-""" Multiply fieldset with some vector x. """
-Base.(:*)(x::Array{Float64, 1}, f::Array{Field}) = sum(x .* f)
 
-""" Add new field to fieldset. """
-function add_field!(fs::FieldSet, field::Field)
-    push!(fs, field)
+
+""" FieldSet is set of fields, each field can have different time and/or increment. """
+type FieldSet
+    name :: Symbol
+    fields :: Array{Field, 1}
 end
+""" Initializer for FieldSet. """
+function FieldSet(field_name)
+    FieldSet(Symbol(field_name), [])
+end
+function FieldSet()
+    FieldSet(Symbol("unknown field"), [])
+end
+""" Add new field to fieldset. """
+function Base.push!(fs::FieldSet, field::Field)
+    push!(fs.fields, field)
+end
+""" Multiply fieldset with some vector x. """
+Base.(:*)(x::Array{Float64, 1}, fs::FieldSet) = sum(x .* fs.fields)
+""" Get length of a fieldset. """
+function Base.length(fieldset::FieldSet)
+    length(fieldset.fields)
+end
+""" Return ith field from fieldset. """
+function Base.getindex(fieldset::FieldSet, i::Int64)
+    fieldset.fields[i]
+end
+#""" Return last field from fieldset. """
+function Base.endof(fieldset::FieldSet)
+    length(fieldset)
+end
+
 
 
 """ Basis function. """
@@ -70,7 +96,7 @@ diff(h::Basis) = h.dbasisdxi
 derivative(h::Basis) = h.dbasisdxi
 
 
-# convenient functions
+# convenient functions -- maybe this is not correct place for them
 """ Evaluate basis function in point ξ. """
 call(b::Basis, xi) = b.basis(xi)
 #""" Interpolate field (h*f)(ξ) """