<?xml version="1.0"?>
<oembed><version>1.0</version><provider_name>Centre for Logistics and Sustainability Analytics</provider_name><provider_url>https://research.kent.ac.uk/celsa</provider_url><author_name>Ramin Raeesi</author_name><author_url>https://research.kent.ac.uk/celsa/author/rr394/</author_url><title>Integrated Charging Network Design (FAST-ICNET) - Centre for Logistics and Sustainability Analytics - Research at Kent</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="2XjBn2jxaz"&gt;&lt;a href="https://research.kent.ac.uk/celsa/integrated-charging-network-design-fast-icnet/"&gt;Integrated Charging Network Design (FAST-ICNET)&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://research.kent.ac.uk/celsa/integrated-charging-network-design-fast-icnet/embed/#?secret=2XjBn2jxaz" width="600" height="338" title="&#x201C;Integrated Charging Network Design (FAST-ICNET)&#x201D; &#x2014; Centre for Logistics and Sustainability Analytics" data-secret="2XjBn2jxaz" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script type="text/javascript"&gt;
/* &lt;![CDATA[ */
/*! This file is auto-generated */
!function(d,l){"use strict";l.querySelector&amp;&amp;d.addEventListener&amp;&amp;"undefined"!=typeof URL&amp;&amp;(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&amp;&amp;!/[^a-zA-Z0-9]/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret="'+t.secret+'"]'),o=l.querySelectorAll('blockquote[data-secret="'+t.secret+'"]'),c=new RegExp("^https?:$","i"),i=0;i&lt;o.length;i++)o[i].style.display="none";for(i=0;i&lt;a.length;i++)s=a[i],e.source===s.contentWindow&amp;&amp;(s.removeAttribute("style"),"height"===t.message?(1e3&lt;(r=parseInt(t.value,10))?r=1e3:~~r&lt;200&amp;&amp;(r=200),s.height=r):"link"===t.message&amp;&amp;(r=new URL(s.getAttribute("src")),n=new URL(t.value),c.test(n.protocol))&amp;&amp;n.host===r.host&amp;&amp;l.activeElement===s&amp;&amp;(d.top.location.href=t.value))}},d.addEventListener("message",d.wp.receiveEmbedMessage,!1),l.addEventListener("DOMContentLoaded",function(){for(var e,t,s=l.querySelectorAll("iframe.wp-embedded-content"),r=0;r&lt;s.length;r++)(t=(e=s[r]).getAttribute("data-secret"))||(t=Math.random().toString(36).substring(2,12),e.src+="#?secret="+t,e.setAttribute("data-secret",t)),e.contentWindow.postMessage({message:"ready",secret:t},"*")},!1)))}(window,document);
//# sourceURL=https://research.kent.ac.uk/celsa/wp-includes/js/wp-embed.min.js
/* ]]&gt; */
&lt;/script&gt;
</html><thumbnail_url>https://research.kent.ac.uk/celsa/wp-content/uploads/sites/2077/2021/12/Electric-Car.jpg</thumbnail_url><thumbnail_width>750</thumbnail_width><thumbnail_height>493</thumbnail_height><description>This project will develop a proof-of-concept planning model for central planners to optimally locate electric vehicles (EVs) charging infrastructure under the risk of disruption to charging points (i.e. unexpected failure, technical faults or breakdowns). The aim of the model will be to maximise total expected traffic volume of EVs that can be charged by an [&hellip;]</description></oembed>
