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Results for “arrival scheduling”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Hybrid PDES Simulation of HPC Networks Using Zombie Packets

Although high-fidelity network simulations have proven to be reliable and cost-effective tools to peer into architectural questions for high-performance computing (HPC) networks, they incur a high resource cost. The time spent in simulating a single millisecond of network traffic in the highest detail can take hours, even for static, well-behaved traffic patterns such as uniform random. Surrogate models offer a significant reduction in runtime, yet they cannot serve as complete replacements and should only be used when appropriate. Thus, there is a need for hybrid modeling, where high-fidelity simulation and surrogates run side-by-side. Here, we present a surrogate model for HPC networks in which: packets bypass the network, while the network state is left untouched, i.e., suspended. To bypass the network, we use historical data to estimate the arrival time at which every packet should be scheduled at; to suspend the network, all in-flight packets are scheduled to arrive at their destinations, and are kept in the system to awaken as zombies when switching back to high-fidelity. Speedup for a hybrid model is relative to the proportion of surrogate to high-fidelity. This light-weight surrogate obtained up to 76× speedup. Keeping the zombies in the network showed an increase in the accuracy of the high-fidelity simulation on restart when compared to restarting the network from an empty state.

HPC networks↗
DOE OSTI2025

EVI-EnSitePy (Electric Vehicle Infrastructure – Energy Estimation and Site Optimization Tool in Python) [EVI-X Modeling Suite] [SWR-25-07]

EVI-EnSitePy is a comprehensive agent-based tool designed for the analysis and design of high-power charging sites, encompassing a wide array of site agents including Electric Vehicles (EVs), chargers, energy storage units (ESS), renewable energy resources (DER), and loads. This versatile tool offers diverse functionalities and a modular modeling approach, allowing detailed configuration of agents based on power ratings, port numbers, energy capacities, demand requirements, charger interfaces, and flexibility to customize the tool for project specific goals. By simulating agent interactions and employing various metrics, EVI-EnSitePy enables the assessment of site performance, exploration of energy management systems (EMS), and implementation of innovative EV charging policies. Utilizing EV charge schedules and arrival states, the tool performs thorough charging site simulations, with outputs consisting of agent and site-level power profiles and statistical metrics. Employing a tree graph structure, EVI-EnSitePy supports nested site structures and power distribution modeling. The tool's ability to generate charging schedules deterministically or via stochastic analysis further enhances its versatility. Through its features and capabilities, EVI-EnSitePy offers a powerful platform for informed decision-making in the realm of high-power charging site design and operation.

Jackson, Derek [National Renewable Energy Laborato↗
DOE OSTI2022

HL-LHC Analysis With ROOT: ROOT Project Input to the HL-LHC Computing Review (Stage 2)

ROOT is high energy physics' software for storing and mining data in a statistically sound way, to publish results with scientific graphics. It is evolving since 25 years, now providing the storage format for more than one exabyte of data; virtually all high energy physics experiments use ROOT. With another significant increase in the amount of data to be handled scheduled to arrive in 2027, ROOT is preparing for a massive upgrade of its core ingredients. As part of a review of crucial software for high energy physics, the ROOT team has documented its R&D plans for the coming years.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Dynamic Resource Management for Parallel Tasks in an Oversubscribed Energy-Constrained Heterogeneous Environment

Abstract: The worth of completing parallel tasks is modeled using utility functions, which monotonically-decrease with time and represent the importance and urgency of a task. These functions define the utility earned by a task at the time of its completion. The performance of such a system is measured as the total utility earned by all completed tasks over some interval of time (e.g., 24 hours). To maximize system performance when scheduling dynamically arriving parallel tasks onto a high performance computing (HPC) system that is oversubscribed and energy-constrained, we have designed, analyzed, and compared different heuristic techniques. Four utility-aware heuristics (i.e., Max Utility, Max Utility-per-Time, Max Utility-per-Resource, and Max Utility-per-Energy), three FCFS-based heuristics (Conservative Backfilling, EASY Backfilling, and FCFS with Multiple Queues), and a Random heuristic were examined in this study. A technique that is often used with the FCFS-based heuristics is the concept of a permanent reservation. We compare the performance of permanent reservations with temporary place-holders to demonstrate the advantages that place-holders can provide. We also present a novel energy filtering technique that constrains the maximum energy-per-resource used by each task. We conducted a simulation study to evaluate the performance of these heuristics and techniques in an energy-constrained oversubscribed HPC environment. With place-holders, energy filtering, and dropping tasks with low potential utility, our utility-aware heuristics are able to significantly outperform the existing FCFS-based techniques.

Energy-Constrained↗
DOE OSTI2020

Expedited Walkdowns and Preparation of Cost Estimates for Decontamination and Demolition of Excess Facilities - 20335

Lawrence Livermore National Security, LLC (LLNS) is the prime contractor responsible for managing and operating Lawrence Livermore National Laboratory (LLNL). The mission of the LLNL is to strengthen security of the United States through development and application of world-class science and technology to enhance the nation's defense, reduce the global threat from terrorism and weapons of mass destruction, and respond with vision, quality, integrity, and technical excellence to scientific issues of national importance. To accomplish its mission, LLNL must plan and manage its campus space and facilities to optimize use of its relatively small one-square-mile footprint. LLNL currently has numerous excess facilities that require decontamination and demolition (D and D). The LLNL Legacy Facility Program is responsible for stewardship and risk reduction programs to effectively manage these excess assets at LLNL. The Legacy Facility Program identified 10 excess facilities at LLNL that were candidates for demolition based on risks from further degradation of the facilities, potential exposure to hazardous materials, or need for removal to make way for new program facilities. The buildings range from a structure built in 1943 to serve as a US Navy drill hall during World War II, to a facility that provided neutrons to study material properties for the fusion energy program. The National Nuclear Security Administration (NNSA) appropriated FY19 funding for the development of Class 3 estimates for these 10 excess facilities that would be used to develop a Program Management Plan for funding consideration. Class 3 estimates are not conceptual, nor overly detailed, but adequate to be used for budget and appropriation purposes. Using existing strategic sourcing agreements, LLNL was able to organize a team of senior subject matter experts (SMEs) with diverse technical backgrounds across the Department of Energy (DOE) Complex to complete extensive process knowledge (PK) reviews and walk-downs of each excess facility and to deliver accurate and complete estimates under an expedited schedule (i.e., within eight weeks). To facilitate the expedited schedule, LLNL was fully prepared for the arrival of the JGMS team, which consisted of the following companies: J.G. Management Systems, Inc. (JGMS); Strata-G, LLC; and Michael Baker International. LLNL provided background and PK information on the excess facilities, pictures, supporting historical documentation, and radiological survey history as well as escorted access to the facilities. The JGMS team has previous experience supporting Program Management Plans for excess facilities at the Y-12 National Security Complex. The team mobilized to LLNL and performed the facility walk-downs from January 22-25, 2019. Using a methodical evaluation process, expertise, and experience, the team was able to deliver walk-down draft reports and estimates to LLNL before their February 8, 2019 deadline. LLNL then in turn reviewed, completed the estimates by adding waste management costs and other LLNL costs, and delivered the estimates to NNSA by February 15, 2019. The completed final reports, including draft D and D estimates, were delivered to LLNL before their March 6, 2019 deadline. The work was successfully completed ahead of the expedited schedule required by LLNL, resulting in a commendation from the client. This paper describes how the partnership and collaboration as a fully integrated team comprised of the prime contractor, LLNS, and the JGMS team successfully met the needs of the US government, resulting in the performance of expedited site walk-downs, the development of summary evaluation reports, and the preparation of draft Class 3 estimates and preliminary schedules for the D and D of 10 excess facilities at LLNL. The efforts of the team will enable the D and D of the first excess facility in the 2020-2021 time frame. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Shared automated vehicle fleet operations for first-mile last-mile transit connections with dynamic pooling

Shared automated vehicles (SAVs) have the potential to promote transit ridership by providing efficient first-mile last-mile (FMLM) connections through reduced operational costs to fleet providers and lower out-of-pocket costs to riders. To help plan for a future of integrated mobility, this paper investigates the impacts of SAVs serving FMLM connections, as a mode that provides flexibility in access/egress decisions and is well coordinated with train station schedules. To achieve this objective, a novel dynamic pooling algorithm was introduced to match SAVs with riders while coordinating the riders' arrival times at the light-rail station to a known train schedule. Microsimulations of SAVs and travelers throughout two central Austin neighborhoods show how larger service areas, higher levels of SAV demand, and longer arrival times between successive trains require larger SAV fleet sizes and higher SAV utilization rates to deliver close traveler wait times. Four-person SAVs appear to perform similar to 6-seat SAVs but will cost less to provide. Using a dynamic pooling algorithm tightly coordinated with train arrivals (every 15 min) delivers 87% of travelers to their stations in time to catch the next train, whereas uncoordinated assignments deliver just 58% of travelers in time.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Methods for multitasking among real-time embedded compute tasks running on the GPU: Methods for Multitasking Real-time Embedded GPU Computing Tasks

Here, we provide an extensive survey on wide spectrum of scheduling methods for multitasking among graphics processing unit (GPU) computing tasks. We then design several schedulers and explain in detail the selected methods we have developed to implement our scheduling strategies. Next, we compare the performance of schedulers on various workloads running on Fermi and Kepler architectures and arrive at the following major conclusions: (1) Small kernels benefit from running kernels concurrently. (2) The combination of small kernels, high-priority kernels with longer runtimes, and lower-priority kernels with shorter runtimes benefits from a CPU scheduler that dynamically changes kernel order on the Fermi architecture. (3) Because of limitations of existing GPU architectures, currently CPU schedulers outperform their GPU counterparts. We also provide results and observations obtained from implementing and evaluating our schedulers on the NVIDIA Jetson TX1 system-on-chip architecture. We observe that although TX1 has the newer Maxwell architecture, the mechanism used for scheduler timings behaves differently on TX1 compared to Kepler leading to incorrect timings. In this paper, we describe our methods that allow us to report correct timings for CPU schedulers running on TX1. Lastly, we propose new research directions involving the investigation of additional scheduling strategies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A Mobility-Driven Approach to Modeling Building Energy

Buildings are one of the primary energy consumers in any city's energy use [12]. Presence and absence of humans is a major contributing factor to the energy use in a building. In this paper, we present an approach to generating a realistic model of human building occupancy throughout a typical work week. We use the Toolbox for Urban Mobility Systems (TUMS) to generate a synthetic population based on population distribution estimates, we schedule the population's daily commute based on National Household Travel Survey (NHTS) survey data, and we simulate their daily travel patterns using an agent-based transportation simulation (TRANSIMS). We process and fuse the simulation output to produce a list of the first and last seen location of each agent in the simulation. Based on the arrival at the last destination, we map each agent to one of the nearby buildings. Using these agent arrivals, as well as NHTS data, we create an hourly occupancy schedule for each building. We successfully demonstrate this workflow at the example of the Chicago Loop, a major business district in Chicago, Illinois.

Berres, Andy↗
DOE OSTI2022

Generating traffic-based building occupancy schedules in Chattanooga, Tennessee from a grid of traffic sensors

Building occupancy significantly impacts energy use, timing for demand impacts, and is a significant source of uncertainty in building energy models. There are relatively few sources that define building occupancy schedules and number of occupants per building or space type. More importantly, these sources define traditional schedules that are likely not to reflect the true occupancy of a given building. We construct traffic-based occupancy schedules which are more responsive to changes in mobility patterns, and which can realistically estimate occupant arrivals, departures, and counts in individual buildings.

Berres, Andy↗
DOE OSTI2020

Radiological Recovery Logistics Tool - 20161

Argonne is building and testing a tool, the Radiological Recovery Logistics Tool (RRLT), that can be used during the response and recovery from a radiological or nuclear incident to effectively allocate appropriate commercial and public works equipment to mitigate, remove, and contain radiological contamination. The requirements for this tool - as well as development of the resulting software - is overseen by a steering committee of stakeholders from DHS's National Urban Security Technology Laboratory (NUSTL), the Federal Emergency Management Agency (FEMA), and the Environmental Protection Agency (EPA). One essential requirement is for RRLT to support the efficient and appropriate allocation of resources for a radiological response. Subsequent discussions between ANL and stakeholders have solidified the nature of this support to include identification of the types of resources to be allocated. The study reported in this paper has both factored fundamental concepts and connections out of this identification process and created a Knowledge Base detailing support goals, response scenarios, and efficacy information on dozens of equipment types. In short, RRLT will dynamically apply these findings to situational conditions surrounding contamination incidents. RRLT's Domain, the model of elements, ideas and relationships with which the tool will work, draws concepts from technical reports and stakeholder vocabularies to connect response goals and scenarios to types of equipment that offer utility towards those goals in those scenarios. RRLT's Knowledge Base will contain details on dozens of equipment types and facilitate the operator's discovery and consumption of these details most pertinent to a dynamically selected subset of goals. The core of its Domain Model is based on a report authored by this team. This report [1] contains a comprehensive list of proposed equipment to accomplish various missions or scenarios that might arise after a large-scale radiological contamination incident in an urban environment or critical infrastructure. The report divides potential response and recovery efforts into five support goals: Survey and monitoring of the contaminated area; Mitigation of received dose to first responders: Decontamination (gross and final) of buildings, vehicles, roadways, parks, and other surfaces: Waste management of solid waste generated during recovery operations: and Containment of wastewater and other waste generated during the response and recovery phases. RRLT's development is driven by use cases. A use case is an intention with which a user approaches the software. Use cases are grouped into delivery increments to schedule development, testing, and presentation to stakeholders. This model partitions the system into seven increments: User Arrival and Authentication, Search and Navigation, Equipment Recommendation, Plan Management, Content Management, and Expanded Access. Once a user 15 authenticated, RRLT will present the user with a dashboard that allows them to explore or search RRLT's content. The dashboard will also include a 'Plan' panel for collecting decisions and relevant observations about an incident at hand to facilitate development of an equipment list. RRLT will offer three general modes of access to items in the knowledge base: - Keyword search for direct discovery of items, - Navigation along predetermined paths from recovery goal towards equipment types, and - Interactive guidance towards equipment types by an autonomous software agent: the Equipment Recommendation Wizard. This presentation will detail progress in the development of the RRLT and also discuss opportunities for those interested in providing feedback on its content and functionality. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Ride Pingo to Transit

In this project, we developed an on-demand microtransit first- and last-mile service. To integrate the service with fixed-route transit, we developed a feature called Transit Connect that prioritized riders’ on-time arrival at the transit station over other service requirements. We first prototyped service and related algorithms in a simulated environment, and then piloted the service in the city of Kent, Washington. Our algorithm incorporates request-specific hard drop-off deadlines to ensure timely arrivals for transit transfers. In the pilot, these constraints were obtained from GTFS Realtime data to accurately determine the schedule of the transit and the location of the stations. This approach introduced the ability to accept or decline new requests based on the timing of transit connections for these new requests and connection status of onboarding customers. The pilot (called “Ride Pingo to Transit”) deployed a fleet of three 14-person vans, ran from September 2021 to March 2023, and served a total of 21,329 trips. Transit Connect was offered for drop-offs at both Kent Station and the Kent Valley hub. In total, 2,844 such trips were completed. This dataset was collected from our pilot, which includes the following: - Requests: List of all trip requests, including those that were actually served and those not materialized. - Fleet: Daily vehicle service logs. - Service details: Daily vehicle stop logs (boarding and alighting). - Trip types: First mile, last mile, or point-to-point. ![pingo to transit](pingo-to-transit.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

FutureGen 2.0 Oxy-combustion Large Scale Test – Final Report

The primary objectives of the FutureGen 2.0 CO 2 Oxy-Combustion Large Scale Test Project were to site, permit, design, construct, and commission, an oxy-combustion boiler, gas quality control system, air separation unit, and CO 2 compression and purification unit, together with the necessary supporting and interconnection utilities. The project was to demonstrate at commercial scale (168MWe gross) the capability to cleanly produce electricity through coal combustion at a retrofitted, existing coal-fired power plant; thereby, resulting in near-zeroemissions of all commonly regulated air emissions, as well as 90% CO 2 capture in steady-state operations. The project was to be fully integrated in terms of project management, capacity, capabilities, technical scope, cost, and schedule with the companion FutureGen 2.0 CO 2 Pipeline and Storage Project, a separate but complementary project whose objective was to safely transport, permanently store and monitor the CO 2 captured by the Oxy-combustion Power Plant Project. The FutureGen 2.0 Oxy-Combustion Large Scale Test Project successfully achieved all technical objectives inclusive of front-end-engineering and design, and advanced design required to accurately estimate and contract for the construction, commissioning, and start-up of a commercial-scale "ready to build" power plant using oxy-combustion technology, including full integration with the companion CO 2 Pipeline and Storage project. Ultimately the project did not proceed to construction due to insufficient time to complete necessary EPC contract negotiations and commercial financing prior to expiration of federal co-funding, which triggered a DOE decision to closeout its participation in the project. Through the work that was completed, valuable technical, commercial, and programmatic lessons were learned. This project has significantly advanced the development of near-zero emission technology and will be helpful to plotting the course of, and successfully executing future large demonstration projects. This Final Scientific and Technical Report describes the technology and engineering basis of the project, inclusive of process systems, performance, effluents and emissions, and controls. Further, the project cost estimate, schedule, and permitting requirements are presented, along with a project risk and opportunity assessment. Lessons-learned related to these elements are summarized in this report. Companion reports Oxy-combustion further document the accomplishments and learnings of the project, including: A.01 Project Management Report which describes what was done to coordinate the various participants, and to track their performance with regard to schedule and budget B.02 Lessons Learned - Technology Integration, Value Improvements, and Program Management, which describes the innovations and conclusions that we arrived upon during the development of the project, and makes recommendations for improvement of future projects of a similar nature . B.03 Project Economics, which details the capital and operation costs and their basis, and also illustrates the cost of power produced by the plant with certain sensitivities. B.04 Power Plant, Pipeline, and Injection Site Interfaces, which details the interfaces between the two FutureGen projects B.05 Contractual Mechanisms for Design, Construction, and Operation, which describes the major EPC, and Operations Contracts required to execute the project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Constant Rate Production: DOE Approach to Meeting NASA Needs for RPS for Nuclear-Enabled Launches.

The use of radioisotope power systems (RPS) for nuclear-enabled NASA missions is a long-standing arrangement between DOE and NASA. The requirements for the power system come from NASA, while DOE performs the procurement, fueling, testing and delivery. Recent examples include Mars Science Laboratory and New Horizons. A challenge has been interplay between the schedule for RPS availability from DOE versus the schedule NASA has for competitively selected missions. By mutual agreement, the actual operations to procure an RPS and prepare it for fueling, has always waited until the final selection of a mission. This timeline for a New Frontiers class mission leaves approximately 5-6 years from the time of final mission selection to the actual launch date. The number of RPS used for a Frontier class mission can be 1 to 3 units, i.e., the recent New Frontiers-2025 announcement of opportunity published in December 2016. If 1 or 2 units are needed for a specific mission, the timeline from the decision point to the launch date is a challenge, but doable. The activities taking place in this timeframe would include manufacturing the power system, producing the fuel, and performing the assembly/testing and delivery operations. If the mission selected requires 3 RPS the logistics of accomplishing all activities during the 5-6 years is problematic. The challenge involves appropriate resourcing for plutonium production, heat source production and assembly/testing operations. Typically, the time between RPS-enabled missions involve staffing attrition and reduction at the heat source production and the assembly/testing facilities that can be down to 60-75 percent of peak staffing levels to reduce costs. The duration for increasing staffing in these areas, which includes hiring, nuclear workforce training and obtaining the appropriate security clearance is 2 years. Taking account for this 2 years and the 6 months prior to launch arrival of the RPS at Kennedy Space Center erodes too much of the 5-6 years to comfortably support the use of 3 RPS on a mission and doesn't leave much schedule margin for a 2 RPS unit mission. To provide better support for NASA nuclear-enabled missions a different approach was devised, constant rate production. This involves a higher level of base capability at Los Alamos National Laboratory (LANL), Idaho National Laboratory (INL) and Oak Ridge National Laboratory (ORNL) to provide a stabilized work force. This will enable 10-15 heat sources to be produced annually at LANL, and subsequently shipped to the INL to be placed into a stable intermediate form that enables storage for up to several years that leads to quick production of general purpose heat source modules when a mission is selected. The up-front production of Pu-238 at ORNL is maintained so that there is material constantly in the pipeline. Production of key specialized components at ORNL is also maintained using this model. This allows for a reduction of risk to the nuclear-enabled missions, yet always having quantities of hardware available “on the shelf” to support production of RPS for NASA.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Fleet-wide Electrification Impacts Assessment for the Valley Transportation Authority

This report explores the long-term electrification opportunities for the Valley Transit Authority’s (VTA) transit bus fleet. The potential for transit bus electrification at VTA as well as the economic impacts of partial and complete electrification are explored. We use the Revenue Operation and Device Optimization model to determine the optimal charging, operation and lowest capital and operating cost solution to achieve different levels of electrification to meet their existing routes. This study finds that, relying on only depot charging, around 70% of the daily trips by VTA’s transit bus fleet can be replaced with battery electric buses (BEBs) today. The benefits and drawbacks of five methods for improving the electrification potential beyond that achievable with only depot charging are discussed including (1) increase charger power, (2) purchase of larger vehicle batteries, (3) en-route charging, (4) purchasing additional buses and swapping them to enable the existing routes/blocks1 to be met, and (5) route/block redesign. A strategy is developed to enable full fleet electrification by increasing charger power or allowing intraday charging as a proxy for the options mentioned above. This method allows us to develop an understanding of the impacts and trade-offs of full fleet electrification. Two charging strategies are examined. Immediate charging, when the bus is charged as soon as it arrives at a depot or en-route charging station, and smart charging, which uses a controller to determine the best times to charge to achieve the lowest charging cost, while maintaining the same trip schedules. Smart charging is effective at reducing the peak power consumption, which can be reduced by between 31% and 65% compared to immediate charging. This translates directly to lower electricity demand charges and lower costs for possible distribution system upgrades. The total lifetime net present value (NPV) costs for different scenarios are presented in Figure ES-1. Scenarios are separated into three sections. The first stacked bar on the left is the base case (business-as-usual) where all buses are diesel hybrids, the next four bars include partial and full fleet electrification utilizing only immediate charging, and the last four bars include partial and full fleet electrification utilizing smart charging. The results show that smart charging scenarios are within ±4% of the lifetime NPV cost of the diesel-hybrid only (business-as-usual) scenario. The scenarios with full fleet electrification (i.e., including intraday charging) are 4% lower cost and those with partial fleet electrification (i.e., without intraday charging) are 2%–3% higher. However, it is important to note that the intraday charging scenarios do not include any additional costs for the equipment necessary to achieve intraday charging (e.g., additional chargers, larger batteries, new route design). Additionally, it is worth noting that the Low Carbon Fuel Standard (LCFS) credit received for implementing electric buses is essential to achieving these results.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Study of Proton Stopping and Energy Deposition in Warm Dense Matter

This grant supported target fabrication and travel costs for Experiment LQ91 at the Matter in Extreme Conditions endstation (MEC) of the SLAC National Accelerator Laboratory’s Linac Coherent Light Source (LCLS). LQ91 was the first experiment to study proton-heated Warm Dense Matter (WDM) with the MEC end station. It was scheduled as the first experiment in MEC following maintenance and upgrades to the optical high intensity laser during LCLS Run 16. The team consisted of scientists, postdocs, and Ph.D. students from UC San Diego and Stanford University divided into two overlapping shifts. The team arrived onsite during the optical intense laser commissioning time to setup and stayed until the end of the experiment culminating in five shifts of awarded LCLS beam time. Postdoc Mathieu Bailly-Grandvaux led preparations in the months leading up to the experiment. During the experiment and in subsequent analysis work, two other UC San Diego postdocs and five UC San Diego graduate students were heavily involved. In this way, the project provided invaluable hands-on training opportunities in high energy-density science for several early-career scientists.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Challenges and Opportunities for HVAC + Phase Change Material Thermal Energy Storage in Buildings

Phase-change material (PCM) thermal-energy storage (TES) integrated with HVAC and domestic hot water (DHW) can shift a large share of building thermal loads. By flattening and shifting loads, PCM TES reduces peak electricity use, eases stress on local and grid infrastructure, and lowers costs. It can also defer costly upgrades to service panels, distribution, and transmission. Higher energy density relative to chilled or hot water storage makes PCM TES practical for small, space limited, and retrofit projects, while packaged HVAC-integrated systems expand cost-effective load shifting to commercial buildings that previously lacked options. Despite this promise, deployment faces barriers. This paper presents challenges, opportunities, and lessons learned from lab and field integrations of PCM TES with packaged HVAC systems. Key challenges include misalignment between default heat pump controls tuned for direct-to-load operation and TES charge/discharge objectives, PCM properties that diverge from manufacturer claims and evolve with cycling, and high integration and deployment costs with off-the-shelf products. These studies underscore the need for factory built, integrated systems that arrive as prepackaged modules with proven controls, reducing design and installation effort and delivering predictable performance across projects. The paper outlines steps to enable viable and scalable PCM TES HVAC and DHW systems, including 1) validated methods that can be used to characterize PCM properties and TES system performance, 2) supervisory controls that optimize charge/discharge scheduling, and 3) factory integrated packaging that eliminates bespoke field engineering.

Dutton, Spencer↗
DOE OSTI2017

A two-stage stochastic optimization model for scheduling electric vehicle charging loads to relieve distribution-system constraints

Electric vehicles (EVs) hold promise to improve the energy efficiency and environmental impacts of transportation. However, widespread EV use can impose significant stress on electricity-distribution systems due to their added charging loads. This paper proposes a centralized EV charging-control model, which schedules the charging of EVs that have flexibility. This flexibility stems from EVs that are parked at the charging station for a longer duration of time than is needed to fully recharge the battery. The model is formulated as a two-stage stochastic optimization problem. The model captures the use of distributed energy resources and uncertainties around EV arrival times and charging demands upon arrival, non-EV loads on the distribution system, energy prices, and availability of energy from the distributed energy resources. We use a Monte Carlo-based sample-average approximation technique and an L-shaped method to solve the resulting optimization problem efficiently. We also apply a sequential sampling technique to dynamically determine the optimal size of the randomly sampled scenario tree to give a solution with a desired quality at minimal computational cost. Here, we demonstrate the use of our model on a Central-Ohio-based case study. We show the benefits of the model in reducing charging costs, negative impacts on the distribution system, and unserved EV-charging demand compared to simpler heuristics. Lastly, we also conduct sensitivity analyses, to show how the model performs and the resulting costs and load profiles when the design of the station or EV-usage parameters are changed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

IP-2 Steam Generator Lower Assembly Packaging, Transport and Disposal - 16510

WMG, Inc. led a team of industry experts in the first of its kind packaging, transportation and disposal of four (4) Steam Generator Lower Assemblies (SGLAs). The project had a number of significant challenges including qualifying the SGLAs as IP-2 packages, implementing roadway improvements and orchestrating the use of three different modes of transportation. In the end, these SGLAs would be the first large components disposed at the WCS Disposal facility in Andrews Texas. The client was re-purposing the SGLA storage mausoleum for 'Fukushima equipment' preparedness so it became necessary to dispose of the assemblies. The WMG team needed to: - Dismantle the mausoleum to allow removal of the SGLAs, - Design, fabricate, deliver and install IP-2 SGLA packaging, and - Transport the packaged SGLAs from the client to the WCS facility for disposal. After qualifying the packaging as IP-2 containers, the SGLAs were loaded onto special equipment for over-the-road transport to the harbor in Kewaunee, WI. Following trans-load, the SGLAs were barged down Lake Michigan through the Mississippi River to the Port of Houston for another trans-load. The SGLAs arrived by rail at WCS' Andrews TX facility. Each transport segment required coordination for transport clearances, proper marking, labeling and placarding for that particular mode of transport as well as coordination with the team involved in moving the large packages from one conveyance to another. The project was completed with zero safety issues, significantly below dose goals, ahead of schedule, and within budget. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗