31:T1292,characterization = { const config = { height: 520, width: 960, units: unitSelection.unit, label: `${unitSelection.unit === "IP" ? "kBTU/ft²/yr": "kWh/m²/yr"}` }; const svg = d3.select(DOM.svg(config.width, config.height)); const graph = sankey(sankey_data); const nodeWidth = graph.nodes[0].x1 - graph.nodes[0].x0; const node = svg.selectAll("g") .data(graph.nodes) .enter().append("g") .attr('transform', d => `translate(${d.x0}, ${d.y0})`); node.append("rect") .attr("height", d => d.y1 - d.y0) .attr("width", d => d.x1 - d.x0) .attr("fill", d => color(d.name)) .attr("display", d => d.name === "Nothing" ? "none" : null) .attr("stroke", "#000") .append("title") .html(d => `${d.name}\n${eui(d.value)} ${config.label}`); node.append("text") .style("font", "10px sans-serif") .attr("x", d => d.x0 < config.width / 2 ? 6 + (d.x1 - d.x0) : - 6) .attr("y", d => (d.y1 - d.y0) / 2) .attr("dy", "0.35em") .attr("text-anchor", d => d.x0 < config.width / 2 ? "start" : "end") .attr('font-size', 10) .html(d => d.name); node.append("text") .style("font", "12px sans-serif") .attr("x", d => d.x0 < config.width / 2 ? 6 + (d.x1 - d.x0) : - 6) .attr("y", d => (d.y1 - d.y0) / 2) .attr("dy", d => { // switch(d.name) { // case "Heating Load": // return "-1.25em"; // default: // return "1.85em"; // } return "1.8em"; }) .attr("text-anchor", d => d.x0 < config.width / 2 ? "start" : "end") .style("font-weight", "bold") .html(d => { console.log(d); switch(d.name) { case "Natural Gas": return `EUI: ${_.round(eui(d.value), 0)} ${config.label}`; case "Electricity": return `EUI: ${_.round(eui(d.value), 0)} ${config.label}`; case "Heating Load": let source = d.targetLinks.filter(dd => dd.source.name === "Heating System"); return `Heating TEDI: ${_.round(eui(source[0].value), 0)} ${config.label}`; default: return ""; } }); node.attr('cursor', 'move') .call(d3.drag() .on('start', dragStart) .on('drag', dragMove) .on('end', dragEnd)); const link = svg.append("g") .attr("fill", "none") .attr("stroke-opacity", 0.5) .selectAll("g") .data(graph.links) .enter().append("g") .style("mix-blend-mode", "multiply") .attr("id", d => d.source.name.replace(" ", "_") + "_" + d.target.name.replace(" ", "_")); //apply gradients based on input and output const gradient = link.append("linearGradient") .attr("id", d => (d.uid = DOM.uid("link")).id) .attr("gradientUnits", "userSpaceOnUse") .attr("x1", d => d.source.x1) .attr("x2", d => d.target.x0); gradient.append("stop") .attr("offset", "0%") .attr("stop-color", d => color(d.source.name)); gradient.append("stop") .attr("offset", "100%") .attr("stop-color", d => color(d.target.name)); link.append("path") .attr("class", "link") .attr("d", d3.sankeyLinkHorizontal()) .attr("stroke", d => d.uid) .attr("display", d=> d.target.name === "Nothing" ? "none": null) .attr("opacity", d => d.value < 0.02 ? 0 : 1) .attr("stroke-width", d => Math.max(1, d.width)); link.append("title") .html(d => `${d.source.name} → ${d.target.name}\n${eui(d.value)} ${config.label}`); function dragStart (d) { if (!d.__x) d.__x = d3.event.x; if (!d.__y) d.__y = d3.event.y; if (!d.__x0) d.__x0 = d.x0; if (!d.__y0) d.__y0 = d.y0; if (!d.__x1) d.__x1 = d.x1; if (!d.__y1) d.__y1 = d.y1; } function dragMove(d) { d3.select(this) .attr('transform', function (d) { const dx = d3.event.x - d.__x; const dy = d3.event.y - d.__y; d.x0 = d.__x0 + dx; d.x1 = d.__x1 + dx; d.y0 = d.__y0 + dy; d.y1 = d.__y1 + dy; if (d.x0 < 0) { d.x0 = 0; d.x1 = nodeWidth; } if (d.x1 > config.width) { d.x0 = config.width - nodeWidth; d.x1 = config.width; } if (d.y0 < 0) { d.y0 = 0; d.y1 = d.__y1 - d.__y0; } if (d.y1 > config.height) { d.y0 = config.height - (d.__y1 - d.__y0); d.y1 = config.height; } return `translate(${d.x0}, ${d.y0})`; }); sankey.update(graph); link.selectAll(".link").attr('d', d3.sankeyLinkHorizontal()); } function dragEnd(d) { delete d.__x; delete d.__y; delete d.__x0; delete d.__x1; delete d.__y0; delete d.__y1; } return svg.node(); }32:T511,md`

### Envelope Sensitivity In addition to overall energy use modeling, parametric analysis was conducted to understand the sensitivity of various envelope characteristics on building energy use. Figure 3 presents these results with the horizontal axes showing incremental changes in the studied parameter, and the vertical axes showing the impact of these changes on building EUI and TEDI. The line represents the overall trend for each parameter, the current proposed values are marked by circles. In accordance with the energy use characterization discussed above, the overall energy use can most benefit from further improvements to wall, roof and door thermal resistance, followed by improvements to window and skylight U values. It is recommended that the design team explore the feasibility of achieving wall and roof performance as close as possible to R50 and R60 respectively, and door, window and skylight performance as close as possible to assembly U:0.25. Finally, an increase in passive solar gains by incorporating a higher SHGC glass can potentially reduce space heating loads, especially for the skylights. Per the energy modeling requirements of ZCB Design Certification, the envelope air infiltration is being modeled at 0.00025 m²/s/m².

`33:T21d3,sensitivies = { //general setup const config = { width: 960, cell: {height: 250, padding:40}, margin: {top: 60, right:10, bottom: 30, left: 40}, cols: 3, format: { "Window U": { newName: "Window U", convert: d => 1/d, ticks: d => d3.format(".2f")(1/d)}, "WWR": { newName: "Window-Wall Ratio", ticks: d3.format(",.0%")}, "Infiltration": { newName: "Infiltration cfm/ft²"}, "Skylight U": { convert: d => 1/d, ticks: d => d3.format(".2f")(1/d)}}, units: unitSelection.unit, y: euiSwitch.y } const tooltip = d3.select("body").append("div") .attr("class", "tooltip3") .style("border-radius", "3px") .style("pointer-events", "none") .style("display", "none") .style("position", "absolute") .style("z-index", "1000") .style("padding", "12px") .style("font-weight", "regular") .style("font-family", "Open Sans") .style("font-size", "12px") .style("background", "white") .style("box-shadow", "0 0 10px rgba(0,0,0,.25)") .style("color", "#333333") .style("line-height", "1.6") .style("pointer-events", "none"); //handles conversion for each variable in config.format const data = sensitivity_data.map(d => { let dd = d.data; for (const key in config.format) { if ("convert" in config.format[key]) { dd = dd.map(p => ({...p, [key]: config.format[key].convert(p[key])})); } } return {variable: d.variable, data: dd}; }); //find the width of cells by dividing the total width by the number of cols config.cell.width = _.round( (config.width - config.margin.left - config.margin.right - config.cell.padding * (config.cols-1)) / config.cols ); //csize the svg based on the number of rows const svg = d3.select(DOM.svg(config.width, (config.cell.height + config.margin.bottom + config.cell.padding) * _.ceil(data.length / 3) + config.margin.top - config.margin.bottom )); //all the y values are the same - could use a map here to get different scales for each small multiple const y = d3.scaleLinear() .domain(d3.extent(data.map(d => d.data.map(p => eui(p[config.y]))).flat())) .range([config.cell.height, 0]).nice(); //create a map for all the x scales const x = new Map( Array.from( data.map(d => d.variable), key => [ key, d3.scaleLinear(d3.extent(data.filter(d => d.variable === key)[0].data.map(d => d[key])), key === "Infiltration" ? [config.cell.width, 0] : [0, config.cell.width]) ] ) ); //create a group for each chart const chart = svg.selectAll("g") .data(data) .join("g") .attr("transform", (d, i) => { //position the group in its appropriate row and col const h = (i % config.cols) * (config.cell.width + config.cell.padding) + config.margin.left; const v = _.floor(i / config.cols) * (config.cell.height + config.margin.bottom + config.cell.padding) + config.margin.top; return `translate(${h},${v})` }); //run through each group chart.each(function(d, i) { //rename the variable if needed let name = d.variable; if (name in config.format) { if ("newName" in config.format[name]){ name = config.format[name].newName; } } //if there are format specifiers, use them, otherwise just use the default let xa = d3.axisBottom(x.get(d.variable)).ticks(6); if (d.variable in config.format) { if ("ticks" in config.format[d.variable]){ xa.tickFormat(config.format[d.variable].ticks); } } const xAxis = g => g .attr("transform", `translate(0,${config.cell.height})`) .call(xa) .call(g => g.select(".domain").remove()); const yAxis = g => { if (i % config.cols === 0) { g.call(d3.axisLeft(y).ticks(6).tickFormat(d3.format(".1f"))) .call(g => g.select(".domain").remove()); } } //put the y axis label in the top left corner of the first row/col. if (i === 0 || i === 3 || i === 6) { d3.select(this).append("g") .attr("transform", "translate(15, 20)") .append("text") .attr("font-size", 10) .attr("text-anchor", "start") .attr("opacity",1) .html(config.units === "IP" ? `${config.y} kBTU/ft²/yr`: `${config.y} kWh/m²/yr`); } //general pattern for generating the interpolation line const line = d3.line() .x(dd => x.get(d.variable)(dd[d.variable])) .y(dd => y(eui(dd[config.y]))) .curve(d3.curveCardinal.tension(0)); //horizontal grid lines d3.select(this).selectAll(".grid .horizontal") .data(_.range(8).slice(1).map(d => d * config.cell.height / 8)) .join("line") .attr("class", "grid") .attr("x1", (i % config.cols != 0) ? -config.cell.padding : 0) .attr("y1", d => d) .attr("x2", config.cell.width) .attr("y2", d => d); //vertical grid lines d3.select(this).selectAll(".grid .vertical") .data(_.range(8).slice(1).map(d => d * config.cell.width / 8)) .join("line") .attr("class", "grid") .attr("x1", d => d) .attr("y1", 0) .attr("x2", d => d) .attr("y2", config.cell.height); d3.select(this).append("g").call(xAxis); d3.select(this).append("g").call(yAxis); d3.select(this).append("rect") .attr("class", "frame") .attr("x", 0) .attr("y", 0) .attr("width", config.cell.width) .attr("height", config.cell.height); //add the variable labels d3.select(this).append("text") .attr("x", 0) .attr("y", -15) .attr("text-anchor", "start") .attr("font-size", 12) .style("font-family", "Open Sans") .html(name); d3.select(this).selectAll(".recommended") .data(d.data.filter(dd => dd.Recommended === "yes")) .join("circle") .attr("class", "recommended") .attr("cx", function(dd) { return x.get(d.variable)(dd[d.variable]); }) .attr("cy", function(dd) { return y(eui(dd[config.y])); }) .attr("r",10) .attr("fill", "#b4d6e8") .attr("opacity", 0.8); d3.select(this).append("path") .datum(d.data) .attr("class", "interpolation") .attr("fill", "none") .attr("stroke", "#1f77b4") .attr("stroke-width", 2) .attr("stroke-linejoin", "round") .attr("stroke-linecap", "round") .attr("d", line); d3.select(this).selectAll("points") .data(d.data) .join("circle") .attr("class", "points") .attr("cx", function(dd) { return x.get(d.variable)(dd[d.variable]); }) .attr("cy", function(dd) { return y(eui(dd[config.y])); }) .attr("r",3) .attr("display", dd => { if (d.variable === "WWR" && dd[d.variable] === 0.35) { return "none"; } else if (d.variable === "Window U" && dd[d.variable] === 1/0.35) { return "none"; } else { return null; } }) .attr("stroke", "#1f77b4") .style("fill", dd => dd.Baseline === "yes" ? "#1f77b4": "#b4d6e8" ); d3.select(this).selectAll("overlay") .data(d.data) .join("circle") .attr("class", "overlay") .attr("r",18) .attr("stroke", "none") .style("fill", "#fff") .style("opacity", 0) .attr("cx", function(dd) { return x.get(d.variable)(dd[d.variable]); }) .attr("cy", function(dd) { return y(eui(dd[config.y])); }) .on("mouseover", dd => { tooltip.style("display", null); let data = dd[d.variable]; if (d.variable in config.format) { if ("ticks" in config.format[d.variable]){ data = config.format[d.variable].ticks(data); } } tooltip.html(`Value: ${data}
${config.y}: ${_.round(eui(dd[config.y]))} ${config.units === "IP" ? "kBTU/ft²/yr": "kWh/m²/yr"} `) .style("left", (d3.event.pageX) + "px") .style("top", (d3.event.pageY - 28) + "px");; }) .on("mousemove", dd => { tooltip .style("left", (d3.event.pageX) + "px") .style("top", (d3.event.pageY - 28) + "px"); }) .on("mouseout", d => { tooltip.style("display", "none"); }); }); return svg.node(); }34:T1d57,parcoords = { const config = { height: 500, width: 960, margin: {top: 60, right: 10, bottom: 10, left: 35}, format: { "Wall R": { ticks: d3.format(".0f"), selection: [225, 300]}, "Roof R": { ticks: d3.format(".0f"), selection: [250, 325]}, "Window U": { ticks: d3.format(".2f"), selection: [250, 325]}, "Skylight U": { ticks: d3.format(".2f"), selection: [250, 325]}, // "Shade Depth": { // reverse: true, // selection: [0, 75], // newName: `Shade Depth (${unitSelection.unit === "IP" ? "ft" : "m"})`, // convert: d => (unitSelection.unit === "IP" ? d : d * 0.3048)}, "Infiltration": { newName: "Infiltration (CFM/ft²)", ticks: d3.format(".2f"), selection: [250, 325]}, // "Infiltration": { // newName: "Infiltration (CFM/ft²)", // selection: [0,75], // ticks: d3.format(".3f")}, "Door R": { ticks: d3.format(".1f"), selection: [175, 250]}, "EUI": { newName: `${unitSelection.unit === "IP" ? "EUI kBTU/ft²/yr": "EUI kWh/m²/yr"}`, anchor: "end", ticks: d3.format(".1f")}, "TEDI": { newName: `${unitSelection.unit === "IP" ? "TEDI kBTU/ft²/yr": "TEDI kWh/m²/yr"}`, anchor: "end", ticks: d3.format(".1f")} }, units: unitSelection.unit }; const container = document.createElement("div"); container.setAttribute("class", "parcoords"); container.setAttribute("style", `width: ${config.width}px; height: ${config.height}px;`); const ctx = DOM.context2d(config.width, config.height); //ctx.transform(1, 0, 0, 1, config.margin.left, config.margin.top); const svg = d3.select(DOM.svg(config.width, config.height)); config.chartHeight = config.height - config.margin.top - config.margin.bottom; config.chartWidth = config.width - config.margin.right - config.margin.left; const dimensions = parametric_data.columns.filter(d => d != "dataset"); const data = parametric_data.map(d => { let dd = d; for (const key in config.format) { if ("convert" in config.format[key]) { dd = {...dd, [key]: config.format[key].convert(dd[key])}; } } return dd; }); const y = new Map( Array.from( dimensions, key => { const reverse = Object.keys(config.format).filter(d => "reverse" in config.format[d]); let range = reverse.indexOf(key) >= 0 ? [0, config.chartHeight] : [config.chartHeight, 0]; return [key, d3.scaleLinear(d3.extent(data, d => d[key]), range).nice()] } ) ); const x = d3.scalePoint().range([0, config.chartWidth]).domain(dimensions).padding(0); const c = svg.append("g").attr("transform", `translate(${config.margin.left}, ${config.margin.top})`); const axis = d3.axisLeft().ticks(5); ctx.globalCompositeOperation = 'darken'; const g = c.selectAll(".dimension") .data(dimensions) .enter().append("g") .attr("class", "dimension") .classed("nonactive", false) .attr("transform", d => `translate(${x(d)})`); g.append("g") .attr("class", "paraxis") .each(function(d) { let ya = axis.scale(y.get(d)); if (Object.keys(config.format).filter(d => "ticks" in config.format[d]).indexOf(d) >= 0) { ya = axis.scale(y.get(d)).tickFormat(config.format[d].ticks); } d3.select(this).call(ya); }) .call(g => g.selectAll("text") .clone(true).lower() .attr("fill", "none") .attr("stroke-width", 4) .attr("stroke-linejoin", "round") .attr("opacity", 0.6) .attr("stroke", "white")) .call(g => g.selectAll("text") .attr("x", -12)); g.append("text") .attr("class", "label") .style("text-anchor", d => { let anchor = "middle"; if (Object.keys(config.format).filter(d => "anchor" in config.format[d]).indexOf(d) >= 0) { anchor = config.format[d].anchor; } return anchor }) .attr("y", -25) .attr("font-size", 12) .style("font-family", "Open Sans") .html(d => { let name = d; if (Object.keys(config.format).filter(d => "newName" in config.format[d]).indexOf(d) >= 0) { name = config.format[d].newName; } return name; }); const render = renderQueue(draw).rate(50); ctx.clearRect(0,0,config.width,config.height); render(data); g.append("g") .attr("class", "parbrush") .each(function(d) { y.get(d).brush = d3.brushY().extent([[-10,-1], [10,config.chartHeight + 1]]) .on("brush", brush) .on("end", brush); d3.select(this) .call(y.get(d).brush); if (Object.keys(config.format).filter(d => "selection" in config.format[d]).indexOf(d) >= 0) { d3.select(this).call(y.get(d).brush.move, config.format[d].selection); } }) .selectAll("rect") .attr("x", -10) .attr("width", 20); function brush() { render.invalidate(); const actives = []; svg.selectAll(".parbrush") .filter(function(d) { y.get(d).brushSelectionValue = d3.brushSelection(this); return d3.brushSelection(this); }) .each(function(d) { actives.push({ dimension: d, extent: d3.brushSelection(this).map(y.get(d).invert) }); }); const selected = data.filter(function(d) { return actives.every(function(active) { let result = active.extent[1] <= d[active.dimension] && d[active.dimension] <= active.extent[0]; const reverse = Object.keys(config.format).filter(d => "reverse" in config.format[d]); if (reverse.indexOf(active.dimension) >= 0) { result = active.extent[1] >= d[active.dimension] && d[active.dimension] >= active.extent[0]; } return result; }); }); ctx.clearRect(0,0,config.width,config.height); render(selected); } function draw(d) { if (d.dataset === "interpolated") { //context.globalAlpha = .1; ctx.strokeStyle = "#ddeaf2"; ctx.lineWidth = 1; } else { //context.globalAlpha = 1; ctx.strokeStyle = "#1f77b4"; ctx.lineWidth = 1.5; } ctx.beginPath(); var coords = dimensions.map(p => [x(p) + config.margin.left, y.get(p)(d[p]) + config.margin.top]); coords.forEach(function(p,i) { // this tricky bit avoids rendering null values as 0 if (p === null) { // this bit renders horizontal lines on the previous/next // dimensions, so that sandwiched null values are visible if (i > 0) { var prev = coords[i-1]; if (prev !== null) { ctx.moveTo(prev[0],prev[1]); ctx.lineTo(prev[0]+6,prev[1]); } } if (i < coords.length-1) { var next = coords[i+1]; if (next !== null) { ctx.moveTo(next[0]-6,next[1]); } } return; } if (i == 0) { ctx.moveTo(p[0],p[1]); return; } ctx.lineTo(p[0],p[1]); }); ctx.stroke(); } container.appendChild(ctx.canvas); container.appendChild(svg.node()); return container; }35:T40b,html``36:T5ff,renderQueue = function(func) { var _queue = [], // data to be rendered _rate = 1000, // number of calls per frame _invalidate = function() {}, // invalidate last render queue _clear = function() {}; // clearing function var rq = function(data) { if (data) rq.data(data); _invalidate(); _clear(); rq.render(); }; rq.render = function() { var valid = true; _invalidate = rq.invalidate = function() { valid = false; }; function doFrame() { if (!valid) return true; var chunk = _queue.splice(0,_rate); chunk.map(func); timer_frame(doFrame); } doFrame(); }; rq.data = function(data) { _invalidate(); _queue = data.slice(0); // creates a copy of the data return rq; }; rq.add = function(data) { _queue = _queue.concat(data); }; rq.rate = function(value) { if (!arguments.length) return _rate; _rate = value; return rq; }; rq.remaining = function() { return _queue.length; }; // clear the canvas rq.clear = function(func) { if (!arguments.length) { _clear(); return rq; } _clear = func; return rq; }; rq.invalidate = _invalidate; var timer_frame = window.requestAnimationFrame || window.webkitRequestAnimationFrame || window.mozRequestAnimationFrame || window.oRequestAnimationFrame || window.msRequestAnimationFrame || function(callback) { setTimeout(callback, 17); }; return rq; }37:[] 2f:{"title":"","cells":[{"id":139,"value":"viewof date = html`August 26, 2019 - Pursuit Phase Energy Analysis`","pinned":false,"hidden":false,"mode":"ojs"},{"id":0,"value":"md`# CPC GTA East Facility`","pinned":false,"hidden":false,"mode":"ojs"},{"id":7,"value":"viewof unitSelection = form(html``)","pinned":false,"hidden":false,"mode":"ojs"},{"id":157,"value":"md`

\n### Introduction\nIntegral Group developed a whole building energy model for the proposed Canada Post Corporation Greater Toronto Area East Facility near Scarborough, ON. The primary purpose of this analysis is the check whether the project design is on track to achieve a Thermal Energy Demand Intensity (TEDI) under ${formatEUI_SI_IP(34)} in compliance with requirements of the Zero Carbon Building (ZCB) Standard published by the Canada Green Building Council (CaGBC) for ASHRAE Climate Zone 6. This study will help evaluate the sensitivity of different envelope component characteristics on building energy use and TEDI. Figure 1 presents a graphic representation of the energy model. This modeling was conducted with all doors in the closed position.

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":231,"value":"md` $\"Solar$ `","pinned":false,"hidden":false,"mode":"ojs"},{"id":224,"value":"viewof figure1 = html`Figure 1: Graphic representation of the energy model.

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":162,"value":"md`\n

\n### Energy End Use Characterization\nFigure 2 below shows the breakdown in energy by end use for the proposed design. Energy sources are aligned on the left side of the graphic, while energy sinks (conduction losses, equipment gains, etc.) are aligned on the right side. The total energy use intensity (EUI) of the Proposed design is approximately ${formatEUI_SI_IP(258.5)}, with 71% of this attributable to equipment loads, followed by 14% to HVAC system fans and about 5% to lighting energy. The load components on the right show the key drivers of proposed design energy use. Internal equipment gains form the largest load component, constituting 86% of the total cooling load. In terms of heating, the proposed design parameters achieve a TEDI of ${formatEUI_SI_IP(2.2)}, with the majority of the load due to envelope losses.

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":34,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":57,"value":"viewof figure2 = html`Figure 2: Building energy use characterization showing load components and energy end-uses for the proposed design.

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":173,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":49,"value":"viewof euiSwitch = form(html``)","pinned":false,"hidden":false,"mode":"ojs"},{"id":64,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":55,"value":"sensLegend = {\n \n const svg = d3.select(DOM.svg(960, 20))\n .style(\"font\", \"11px sans-serif\")\n .style(\"margin-bottom\", \"15px\");\n\n const g = svg.append(\"g\")\n .selectAll(\"g\")\n .data([\"Target\", \"Baseline\"])\n .enter().append(\"g\")\n .attr(\"transform\", (d, i) => `translate(${40}, ${10})`);\n\n g.append(\"circle\")\n .attr(\"r\", d => d === \"Baseline\" ? 3: 10)\n .attr(\"stroke\", d => d === \"Baseline\" ? \"#1f77b4\": \"none\")\n .style(\"fill\", d => d === \"Baseline\" ? \"#1f77b4\": \"#b4d6e8\" )\n .style(\"opacity\", d => d === \"Baseline\" ? 1: .6 );;\n\n g.append(\"text\")\n .attr(\"x\", 20)\n .attr(\"y\", 0)\n .attr(\"dy\", \"0.35em\")\n .text(d => d === \"Baseline\" ? \"Proposed Design\": \"\");\n \n return svg.node();\n}\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":59,"value":"viewof figure3 = html`Figure 3: Sensitivity of individual building performance parameters on building EUI and TEDI.

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":177,"value":"md`\n

\n### Parametric Analysis\nTo better understand the effect of different performance characteristics on building EUI and TEDI, Figure 4 presents a parallel coordinates plot where each of the first six vertical axes represents a performance parameter and its evaluated properties, and the last two axes show the EUI and TEDI resulting from the selected combinations. Putting constraints on one of more attributes, for instance, allows for the exploration of how changing the remaining attributes affects the EUI and TEDI. The dark lines in the chart are results for combinations simulated using the whole building energy model. The lighter lines represent results from all other combinations that are generated using statistical surrogate models that utilize data-driven approximation techniques.

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":82,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":91,"value":"parLegend = {\n \n const svg = d3.select(DOM.svg(960, 60))\n .style(\"font\", \"11px sans-serif\")\n .style(\"margin-bottom\", \"15px\");\n\n const g = svg.append(\"g\")\n .selectAll(\"g\")\n .data([\"Interpolated Data\", \"Modeled Data\"])\n .enter().append(\"g\")\n .attr(\"transform\", (d, i) => `translate(${40}, ${i*24 + 30})`);\n\n g.append(\"line\")\n .attr(\"x1\", 0)\n .attr(\"x2\", 20)\n .attr(\"y1\", 0)\n .attr(\"y2\", 0)\n .attr(\"stroke\", d => d === \"Interpolated Data\" ? \"#ddeaf2\": \"#1f77b4\")\n .attr(\"stroke-linejoin\", \"round\")\n .attr(\"stroke-linecap\", \"round\")\n .attr(\"stroke-width\", 2)\n\n g.append(\"text\")\n .attr(\"x\", 30)\n .attr(\"y\", 0)\n .attr(\"dy\", \"0.35em\")\n .text(d => d);\n \n return svg.node();\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":154,"value":"viewof figure4 = html`Figure 4: Effect of different combinations of parameter properties on building energy use intensity. Move or expand the selection box for each attribute.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":405,"value":"md`\n

\n### Photovoltaic Generation\nThe ZCB standard requires the project to install onsite renewable energy systems to generate a minimum of 5% of the building’s total annual energy consumption. Based on the closed-door energy model results, this translates to an onsite generation requirement of roughly 700 MWh by the PV array. This level of generation will require a 520 kW_p rooftop array on roughly ${unitSelection.unit === \"SI\" ? 5500: _.round(5500*10.76, 0)} ${unitSelection.unit === \"SI\" ? \"m²\": \"ft²\"} of the building roof, as illustrated in Figure 5. In addition to meeting the minimum requirements, Figure 5 also illustrates the sizes and capacities of different PV arrays that will be required to offset 25% and 50% of building energy use.

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":408,"value":"md` $\"Solar$ `","pinned":false,"hidden":false,"mode":"ojs"},{"id":410,"value":"viewof figure5 = html`
Figure 5: PV generation potential of different roof areas.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":244,"value":"md`\n

\nDetailed model input assumptions are documented [here.](https://www.elementa.nyc/projects/canada-post/assets/190826_CPC_EM_Inputs.pdf)

` ","pinned":false,"hidden":false,"mode":"ojs"},{"id":11,"value":"_ = require('lodash@4.17.11/lodash.js').catch(() => window._)","pinned":false,"hidden":false,"mode":"ojs"},{"id":9,"value":"import {form} from \"@mbostock/form-input\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":5,"value":"formatEUI_SI_IP = d => {\n if (unitSelection.unit === \"SI\") {\n return `${d} kWh/m²/yr`;\n }\n else {\n return `${_.round(d * 3.412 / 10.76, 0)} kBtu/ft²/yr`;\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":22,"value":"d3 = require('d3@5.9.2','d3-sankey@0.12.1');","pinned":false,"hidden":false,"mode":"ojs"},{"id":25,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":28,"value":"sankey_data = {\n let sankey_data = (await d3.csv(`https://www.elementa.nyc/projects/canada-post/data/sankey_data_r2.csv?version=${Math.floor(Math.random() * 100)}`)).map(({source, target, value}) => ({source: source, target: target, value: +value}));\n \n //http://elementa.nyc/yale/berekely/data/yale_sankey.csv\n //create a list of nodes and links\n const nodes = Array.from(new Set(sankey_data.map(d => [d.source, d.target]).flat()));\n const links = sankey_data.map(({source, target, value}) => ({\n source: nodes.indexOf(source),\n target: nodes.indexOf(target),\n value: value\n }));\n\n sankey_data = {nodes: nodes.map(d => ({name: d})), links: links};\n return sankey_data;\n} ","pinned":false,"hidden":false,"mode":"ojs"},{"id":31,"value":"sankey = {\n const config = {\n height: 500,\n width: 960,\n margin: {bottom: 10}\n }\n const sankey = d3.sankey()\n .nodeWidth(15)\n .nodePadding(10)\n .extent([[1, 1], [config.width, config.height - config.margin.bottom]])\n .nodeAlign(d3.sankeyLeft);\n return sankey;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":36,"value":"eui = d => (unitSelection.unit === \"IP\") ? _.round(d * 3.412 * 0.092903, 2) : _.round(d, 2);","pinned":false,"hidden":false,"mode":"ojs"},{"id":39,"value":"color = {\n const lookup = {\n \"Electricity\":\"#d6d231\",\n \"Natural Gas\": \"#e55725\",\n \"DHW\":\"#d52928\",\n \"Heating Energy\":\"#d52928\",\n \"Cooling Energy\":\"#1dbfcf\",\n \"Lights\":\"#d6d231\",\n \"Pumps\":\"#adadad\",\n \"Fans\":\"#bfbfbf\",\n \"Equipment\":\"#dddddd\",\n \"Other Gains\":\"#a17eb9\",\n \"Internal Equipment Gains\":\"#a17eb9\",\n \"Other Losses\":\"#a17eb9\",\n \"Wall Losses\":\"#a17eb9\",\n \"OA Cooling\":\"#6aadd6\",\n \"Equipment Gains\":\"#6aadd6\",\n \"Lighting\":\"#6aadd6\",\n \"Solar\":\"#6aadd6\",\n \"Occupants\":\"#6aadd6\",\n \"Cooling Load\":\"#1f77b4\",\n \"Cooling System\":\"#1f77b4\",\n \"Envelope\":\"#f7aa6e\",\n \"Heating Load\":\"#e55725\",\n \"Heating System\":\"#e55725\",\n \"Outside Air Heating\": \"#f7aa6e\"\n };\n\n return name => lookup[name];\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":66,"value":"sensitivity_data = {\n //add a random version number to avoid caching\n let data = (await d3.csv(`https://www.elementa.nyc/projects/canada-post/data/parametric_data_r2.csv?version=${Math.floor(Math.random() * 100)}`, d3.autoType)); \n //group the data by independent variable\n const grouped = group(data, d => d.Variable);\n data = Array.from(grouped, d => ({variable: d[0], data: d[1].sort((a, b) => a[d[0]] - b[d[0]])}));\n return data;\n} ","pinned":false,"hidden":false,"mode":"ojs"},{"id":68,"value":"import {group} from \"@mbostock/group\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":89,"value":"parametric_data = {\n let parametrics = (await d3.csv(`https://www.elementa.nyc/projects/canada-post/data/interpolated_data_r2.csv`, d3.autoType)); \n \n const columns = parametrics.columns;\n const data = parametrics.map(d => ({...d, EUI: eui(d.EUI), TEDI: eui(d.TEDI)}));\n data.columns = columns;\n \n return data;\n} ","pinned":false,"hidden":false,"mode":"ojs"},{"id":86,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W37","stdlib":"1","titling":"auto"}