31:Tb02,viewof zone_tower = { let parent = document.createElement("div"); parent.value = "l6_z2"; let svg = d3.select(DOM.svg(960, 220)); let cover = (await d3.xml(`https://www.elementa.nyc/projects/pmx/data/zones2.svg?version=${Math.floor(Math.random() * 1000)}`).then(data => { svg.node().appendChild(data.documentElement.getElementById("root")); let style = document.createElement("style"); style.innerHTML = data.getElementsByTagName("style")[0].innerHTML; svg.attr("viewBox", data.getElementsByTagName("svg")[0].getAttribute("viewBox")); document.head.appendChild(style); svg.selectAll("#l1_x5F_shadow, #l2_x5F_shadow, #l3_x5F_shadow, #l4_x5F_shadow, #l5_x5F_shadow, #l6_x5F_shadow, #l7_x5F_shadow, #l8_x5F_shadow, #z1_x5F_shadow, #z2_x5F_shadow, #z3_x5F_shadow, #z4_x5F_shadow, #z5_x5F_shadow").classed("hidden", true).classed("clicked", false); svg.selectAll("#l1, #l2, #l3, #l4, #l5, #l6, #l7, #l8") .classed("hidden", true) .classed("clicked", false) .on("mouseover", function(d) { d3.select(this) .style("cursor", "pointer") .classed("hidden", false); }).on("mouseout", function(d) { if (!(d3.select(this).classed("clicked"))) d3.select(this).classed("hidden", true); }).on("click", function(d) { d3.selectAll("#l1, #l2, #l3, #l4, #l5, #l6, #l7, #l8").classed("clicked", false).classed("hidden", true); d3.select(this).classed("hidden", false).classed("clicked", true); // let id = d3.select(this).attr("id"); // d3.select(`#${id}_x5F_shadow`).classed("hidden", false).classed("clicked", true); parent.value = d3.select(this).attr("id") + parent.value.slice(2, 5); parent.dispatchEvent(new CustomEvent("input")); }); svg.selectAll("#z1, #z2, #z3, #z4, #z5") .classed("hidden", true) .classed("clicked", false) .on("mouseover", function(d) { d3.select(this) .style("cursor", "pointer") .classed("hidden", false); }).on("mouseout", function(d) { if (!(d3.select(this).classed("clicked"))) d3.select(this).classed("hidden", true); }).on("click", function(d) { d3.selectAll("#z1, #z2, #z3, #z4, #z5").classed("clicked", false).classed("hidden", true); d3.select(this).classed("hidden", false).classed("clicked", true); // let id = d3.select(this).attr("id"); // d3.select(`#${id}_x5F_shadow`).classed("hidden", false).classed("clicked", true); parent.value = parent.value.slice(0, 3) + d3.select(this).attr("id"); parent.dispatchEvent(new CustomEvent("input")); }); svg.selectAll("#l6, #z2").classed("hidden", false).classed("clicked", true); parent.appendChild(svg.node()); })) return parent; }32:T44c,html``33:[] 2f:{"title":"","cells":[{"id":0,"value":"html`

Integral's Approach

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":761,"value":"md`Our approach to high performance design starts with first principles – understanding the main climatic and programmatic drivers of building energy use. We begin most of our projects with an evaluation of the local site to identify opportunities for passive design strategies. We are constantly asking ourselves, “How can we create comfortable spaces using only the resources available on site?” The example image below is from the Sidewalk Labs project in Toronto, where we started by understanding how to address building massing and orientation.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":905,"value":"md`
$\"Climate$
`","pinned":false,"hidden":false,"mode":"ojs"},{"id":913,"value":"html`

End Use Characterization

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":918,"value":"md`After evaluating programmatic requirements and site constraints, we develop energy models to characterize energy use. This type of analysis allows us to determine what types of design strategies might be most impactful in terms of improving energy performance. The chart below is an example energy use characterization for a research office park in Toronto. Energy sources are aligned on the left side of the graphic, while energy sinks (conduction losses, equipment gains, etc.) are aligned on the right.

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":615,"value":"characterization","pinned":false,"hidden":false,"mode":"ojs"},{"id":497,"value":"html`

Perfomance Optimization

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":774,"value":"md`The next step in our process involves conducting sensitivity analyses for critical building components to set preliminary performance targets. This type of analysis helps to quickly establish benchmarks for energy performance and set preliminary design criteria. The charts below show the results of this analysis for a Post Office building in Canada, with the horizontal axes showing incremental changes in each building component, and the vertical axes showing the impact of these changes on building energy use intensity (EUI) or thermal energy demand intensity (TEDI). The line represents the overall trend for each variable.

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":511,"value":"viewof euiSwitch","pinned":false,"hidden":false,"mode":"ojs"},{"id":517,"value":"sensitivies","pinned":false,"hidden":false,"mode":"ojs"},{"id":474,"value":"html`

Parametric Analysis

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":776,"value":"md`To help the design team navigate the complex tradeoffs that exist with any project, we use statistical models to generate results for thousands of variable combinations from a limited number of simulation runs. The speed and efficiency of this approach helps design teams make quick decisions as they move through the design process. In the parallel coordinates plot below, each of the first six vertical axes represents an envelope performance variable, and the last two axes show the EUI and TEDI resulting from the selected combinations. 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.

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":488,"value":"parcoords","pinned":false,"hidden":false,"mode":"ojs"},{"id":492,"value":"parLegend","pinned":false,"hidden":false,"mode":"ojs"},{"id":441,"value":"html`

Targeted Analysis

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":763,"value":"md`Once we establish the high-level performance targets and create a pathway to achieve our design objectives, we move into more detailed analysis of specific design strategies. For example, for the Sidewalk Labs project in Toronto, the architectural design team wanted a systematic and data-driven approach to designing amenity spaces in the building. Our team helped create a framework for understanding the thermal comfort implications of various envelope options and conditioning strategies. The chart below shows the number of cold discomfort hours (hours when the operative space temperature is below a comfortable level) for each orientation, zone, and envelope strategy. The framework can then be used to make on-the-fly design changes early in the design process without re-running the energy simulations.
`","pinned":false,"hidden":false,"mode":"ojs"},{"id":341,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":138,"value":"tower_series","pinned":false,"hidden":false,"mode":"ojs"},{"id":387,"value":"tower_legend","pinned":false,"hidden":false,"mode":"ojs"},{"id":380,"value":"tower_series.update(zone_tower)","pinned":false,"hidden":false,"mode":"ojs"},{"id":976,"value":"import {series as tower_series, legend as tower_legend} \nwith {zone_tower as zone}\nfrom \"@jwperakis/pmx-amenity-space-analysis\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":546,"value":"html`

Renewables and Battery Optimization

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":783,"value":"md`On-site renewable energy and battery storage are not just afterthoughts in our design process, but integral to the way that we think about net-zero design and decarbonization at scale. We recognize that generation and storage, when properly integrated into a holistic energy strategy, are important components of low-carbon design. The graph below represents the output of a model for the First Nations Technical Institute in Canada, showing the hourly draw on the electric grid given different combinations of renewable energy and battery storage capacities. The starting state of the graph depicts the hourly load profile for average days in the first two months (January and February). Use the context bar below the graph to select different times during the year or use the mouse to zoom and pan on the graph itself to see more information.

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":568,"value":"viewof pv_scenario","pinned":false,"hidden":false,"mode":"ojs"},{"id":571,"value":"viewof pvSize","pinned":false,"hidden":false,"mode":"ojs"},{"id":574,"value":"viewof windSize","pinned":false,"hidden":false,"mode":"ojs"},{"id":577,"value":"viewof batterySize","pinned":false,"hidden":false,"mode":"ojs"},{"id":585,"value":"chart","pinned":false,"hidden":false,"mode":"ojs"},{"id":590,"value":"pv_legend","pinned":false,"hidden":false,"mode":"ojs"},{"id":1010,"value":"html`

District Energy and Geoexchange

`","pinned":true,"hidden":false,"mode":"ojs"},{"id":1012,"value":"md`In addition to building performance optimization and renewable energy integration, Integral specializes in district energy systems to maximize efficiency in multi-building developments. We have a particular expertise in designing ground-coupled low-exergy systems that run entirely on electricity to maximize operational greenhouse gas reductions. The video below is an example of district-scale geo-exchange system for Washington University in St. Louis, demonstrating how the geo field is utilized for heating and cooling and recharged with rooftop solar hot water systems.

`","pinned":true,"hidden":false,"mode":"ojs"},{"id":1014,"value":"html`

`","pinned":true,"hidden":false,"mode":"ojs"},{"id":1028,"value":"md`
$\"Climate$
`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1031,"value":"md`
$\"Climate$
`","pinned":false,"hidden":false,"mode":"ojs"},{"id":613,"value":"import {characterization} from \"@elementa/mcmaster-innovation-park\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":514,"value":"import {sensitivies}\nwith {euiSwitch as euiSwitch}\nfrom \"@jwperakis/cpc-revision-2\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":507,"value":"import {viewof euiSwitch} from \"@jwperakis/cpc-revision-2\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":692,"value":"import {parcoords, parLegend} from \"@jwperakis/canada-post\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":610,"value":"md`
`","pinned":false,"hidden":false,"mode":"ojs"},{"id":583,"value":"import {chart}\nwith {pv_scenario as scenario, pvSize as pvSize, windSize as windSize, batterySize as batterySize}\nfrom \"@elementa/first-nations-technical-institute\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":565,"value":"import {legend as pv_legend, output, viewof scenario as pv_scenario, viewof pvSize, viewof windSize, viewof batterySize}\nfrom \"@elementa/first-nations-technical-institute\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":748,"value":"import {plot as op_plot} from \"@elementa/50-church-street-atrium\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":882,"value":"html`\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":677,"value":"html`

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":343,"value":"d3 = require(\"d3@v5\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":345,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}