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At least 55 records · Page 3

Geographic Information System Based Emergency Response Training Assessments for DOE Radioactive Materials Transport - 20027

Safety and security are priorities of U.S. Department of Energy (DOE) radioactive materials shipping campaigns. In the more than 70-year history of domestic transport of spent nuclear fuel (SNF), there has never been a transportation-related radiological injury. To support transportation planning, among the tools that DOE uses is the Stakeholder Tool for Assessing Radioactive Transportation (START). START contains geospatial data and transportation route analyses capabilities designed to support a range of DOE transportation planning initiatives. One of those functions is the capability to support emergency response planning and training for State and Tribal jurisdictions located on routes used for DOE shipments of radioactive materials. As part of the Department's commitment to public safety, DOE provides federally-funded radiological response training to emergency responders along DOE radioactive materials transportation corridors through its Transportation Emergency Preparedness Program (TEPP). START contains spatial data representing the locations and emergency-response capabilities of fire departments, police, hospitals, State emergency response centers, and where TEPP-trained personnel are based. The START tool supports State and Tribal users' ability to evaluate emergency-response coverage on active and potential DOE radioactive materials transport routes through their jurisdictions, provide expected response times to reach the scene of an incident, identify equipment available to support a response, and identify the number of response personnel and their respective training levels. In addition, START can be used to identify gaps in coverage along a transportation corridor where additional radiological emergency response training may be needed. This paper describes the data, features, and functionality DOE uses to provide a resource for emergency response training needs assessments for States and Tribes along active and potential routes for transporting radioactive materials, and illustrates its use. It also discusses future plans to integrate TEPP and Federal Emergency Management Agency (FEMA) radiological training data to provide a more comprehensive source of geospatial information on personnel who have received equivalent radiological response training. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

CORE-CM in The Greater Green River and Wind River Basins: Transforming and Advancing a National Coal Asset (Final Report)

The following document summarizes project results from “CORE-CM in the Greater Green River and Wind River Basins: Transforming and Advancing a National Coal Asset”. This project is part of the U.S. Department of Energy’s (“DOE”) National Energy Technology Laboratory’s (“NETL”) Carbon Ore, Rare Earth Elements, and Critical Minerals (CORE-CM) Initiative. This report concludes that the Greater Green River and Wind River Basins (GGRB-WRB) Area-of-Interest (AOI 9) is the ideal region for continued research and development in progressing the broader CORE-CM goals outlined by the DOE. Based upon the extensive analyses of technical, social, and community criteria, this report illustrates that the GGRB-WRB hosts numerous potential CORE-CM feedstocks (both coal- and non-coal based), diverse opportunities for utilizing existing industrial waste streams, ample infrastructure and industry to support new CORE-CM-focused technologies, and a highly motivated, well educated, and adaptable workforce to further develop the regional and national CORE-CM supply chain. Additionally, some potential solutions for technological gaps suggest that the GGRB-WRB's diverse resources can play a significant role in achieving the national goal of critical materials independence. With full community participation, meaningful involvement of regional Tribal Nations, and building upon the stakeholder engagement demonstrated here, the GGRB-WRB region presents a unique opportunity for advancing the CORE-CM Initiative. This project was designed to bring together coal-based communities and stakeholders from across the GGRB-WRB to advance new industries for CORE-CM resources. The University of Wyoming (UWyo) School of Energy Resources (SER) led a project team of experts from the Colorado Geological Survey (CGS), Colorado School of Mines (CSM), Los Alamos National Lab (LANL), and local community colleges. Input from basinal, regional, and national experts bolstered the coalition in order to advance the mission of DOE’s CORE-CM initiative and develop the domestic CORE-CM supply chain. Phase I of this project was designed to address the goal of developing and catalyzing economic growth, job creation, and technology innovation in the GGRB-WRB of Wyoming and Colorado, by increasing the supply of CORE-CM to manufacturers of non-fuel Carbon Based Products (CBP) and products reliant upon CM. The GGRB-WRB CORE-CM project worked toward providing benefit through several avenues of performance and research. • Develop a coalition team to achieve project objectives • Complete detailed assessments, including State-of-the-Art (SOTA) Data acquisition of potential CORE-CM materials across the AOI, and meaningfully contributes to DOE’s CORE-CM goals nationally. • Strategic planning for regional economic growth, job creation, and associated technology innovation around coal materials, including plans to maximize the development of potential CORE-CM resources and technology by creating regional public-private partnerships. • Define regional economic growth potential around existing strengths, energy infrastructure, business and industry, including planning for the leveraging of highly trained workforces, existing and novel coal technologies, and energy infrastructure in development of CORE-CM supply chains. • Develop a preliminary strategic plan for increasing the supply of CORE-CM materials to manufacturers of non-fuel Carbon Based Products (CBP) and products reliant upon CM, focusing on regional strengths that result in an emerging diversified CORE-CM economy. • Assemble a committed network of stakeholders and communities that learn about, accept, and grow new energy technologies within coal regions. Additionally, the project team significantly contributed to the CORE-CM Initiative’s national goals, through cross-regional scoping, collaborating with CORE-CM projects in other AOIs, and including parallel regional project experts. In addition to active inclusion and meaningful engagement and contribution to DOE-led working groups, the project team focused on engaging with regional communities including Tribal Nations, economic development groups, and regional government organizations. The project’s CORE-CM development and commercialization plan identified diverse CORECM feedstocks, potential routes towards integration with existing industries, methods for supply-chain development that leverage existing infrastructure and businesses considering the regional economy, identified entry barriers for incorporating traditional and new technologies in those supply chains, recognized opportunities for public-private partnerships to develop technology innovation centers, identified diverse workforces, and conducted stakeholder outreach and education to build a community of understanding on CORE-CM potential in the GGRB-WRB region. Detailed task descriptions can be found in each chapter.

01 COAL, LIGNITE, AND PEAT↗

Commercial Routing Assistance

The Commercial Routing Assistance (CRA) tool merges coordinated and vetted data streams, plots multiple automated or custom routing options, and visualizes the wide variety of state regulations and actions that a driver would encounter along a route. With CRA, commercial operators can plan vehicle movements across multiple states quickly, particularly during emergencies.

Klett, TimothyR.↗

Onboard/Origin-Destination Survey - Phoenix - 2015

Valley Metro conducted an on-board transit survey during spring 2015. This project gathered updated travel behavior data from transit users that encompassed all rail and bus fixed-route services in the Phoenix metropolitan planning area. The study’s goal was to compile statistically accurate information about transit riders and how they use the transit system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

GradientGraph

Under this SBIR Phase II, Reservoir Labs has developed G2 Analytics, a new technology that allows network operators to analyze bottleneck and flow performance with high precision. G2 delivers a new analytical approach and framework to resolve a variety of key problems found in modern communication networks, including: traffic engineering, routing, flow scheduling, network design, capacity planning, resiliency analysis, network slicing, or service level agreement (SLA) management, among others. G2 leverages the bottleneck structure of congestion-controlled communication networks, a recent mathematical discovery by the Reservoir team [RL19b, RL20a, RL20b, RL21a]. Bottleneck structures reveal how perturbations on flows and links propagate through the network, providing an analytical framework to measure (qualitatively and quantitatively) the ripple effects induced as they traverse the network. Leveraging the mathematics of bottleneck structures, Reservoir Labs is developing the G2 technology to provide network operators with a framework to design, optimize and troubleshoot network performance. This delivery includes the G2 software stack.

Yellamraju, Sruthi↗

Curb Allocation and Pick-Up Drop-Off Aggregation for a Shared Autonomous Vehicle Fleet

Advances in information technologies and vehicle automation have birthed new transportation services, including shared autonomous vehicles (SAVs). Shared autonomous vehicles are on-demand self-driving taxis, with flexible routes and schedules, able to replace personal vehicles for many trips in the near future. The siting and density of pick-up and drop-off (PUDO) points for SAVs, much like bus stops, can be key in planning SAV fleet operations, since PUDOs impact SAV demand, route choices, passenger wait times, and network congestion. Unlike traditional human-driven taxis and ride-hailing vehicles like Lyft and Uber, SAVs are unlikely to engage in quasi-legal procedures, like double parking or fire hydrant pick-ups. In congested settings, like central business districts (CBD) or airport curbs, SAVs and others will not be allowed to pick up and drop off passengers wherever they like. This paper uses an agent-based simulation to model the impact of different PUDO locations and densities in the Austin, Texas CBD, where land values are highest and curb spaces are coveted. In this paper 18 scenarios were tested, varying PUDO density, fleet size and fare price. The results show that for a given fare price and fleet size, PUDO spacing (e.g., one block vs. three blocks) has significant impact on ridership, vehicle-miles travelled, vehicle occupancy, and revenue. A good fleet size to serve the region’s 80 core square miles is 4000 SAVs, charging a $1 fare per mile of travel distance, and with PUDOs spaced three blocks of distance apart from each other in the CBD.

Hunter, Christian B.↗

Demand-adaptive Transit Design for Urban Transportation Hubs

In this study, we proposed a novel three-stage framework for planning the optimal demand-adaptive transit (DAT) at urban transportation hubs. Given the potential trip demand and road traffic condition, the proposed framework sequentially generates the optimal set of candidate routes, combines the outgoing routes and incoming routes at the hub, and derives the optimal fleet size and corresponding route frequency under the fixed budget. In particular, we build the route generation algorithm which maximizes passenger demand coverage with travel time deviation constraint. And a heuristic algorithm is further developed which yields near-optimal operation routes for real-time demand. The fleet optimization problem is formulated to minimize the weighted cost of energy savings, operation cost and trip revenue. We conduct comprehensive numerical experiments for planning DAT with electric buses at JFK airport in NYC using NYC taxi and for-hire vehicle trip data and GoogleMap speed data. The results show the superior performance of the proposed route generation algorithm which is able to cover citywide passenger demand with only 61 DAT routes. The results also suggest that the proposed DAT planning framework may serve over 47% of existing taxi and FHV demand by operating 18 routes using the fleet of 62 electric buses.

demand adaptive↗

The Physical and Engineering Limits of Coupled In situ TEM Experiments

Almost all future energy systems (advanced nuclear reactors, fusion energy system, concentrating solar-thermal power (CSP), and wind technologies) are limited by degradation of key material systems exposed to multiple environmental stressors. The degradation during exposure to high temperatures, radiation, mechanical loading, and chemical attack is often dictated by mechanisms active at the microstructural level. The nature of these mechanisms and the associated variations between sequential and concurrent interplay can be explored if the transmission electron microscope (TEM) is utilized as a toolbox for exploration [1]. One such tool developed at Sandia National Laboratories to couple several of these environments is the In situ Ion Irradiation TEM (I3TEM) [2]. Several studies over the last decade utilizing this tool have shown that the scientific intuition developed over decades of sequential experiments is not always a good indicator of concurrent mechanisms or failure routes. This presentation will highlight the recent and planned additions into the I3TEM facility of a Waviks gas injection system and Raman system, respectively, as can be seen in Fig. 1, permitting environmental degradation from gas species leaked into the pole piece region during quantitative mechanical loading (indentation, monotonic loading, high temperature creep, irradiation induced creep, and high-cycle fatigue); multi-beam ion irradiation (energies ranging from 1 keV to 48 MeV and species from H to Au); laser exposure (20 W and 1064 nm), or various combinations thereof that are already possible [3]. This addition permits the facility to explore both sequential or concurrently the four axes of stressors: thermal, mechanical, radiation, and chemical. This information can be directly coupled to modeling, expediting the refinement and validation of both atomistic and mesoscale models.

degradation↗

Integration of High-Z Converter into Full-scale Production Target for Accelerator-based Production of 99 Mo

NorthStar Medical Technologies is planning to produce the 99Mo isotope via the photonuclear route. The Rhodotron accelerator designed by IBA will be used as an electron-beam source. The Rhodotron is an efficient recirculating accelerator, providing low energy dispersion and a low-emittance electron beam. The nominal beam power is assumed to be 120 kW at 40 MeV. In photonuclear production of 99 Mo, a high-power electron beam impinges on a helium-cooled Mo disk target. Electrons are converted into photons through the Bremsstrahlung process. Consequently, high-energy photons interact with the target nuclei, producing 99 Mo through the 100 Mo(γ, n) 99 Mo reaction. Traditionally, photonuclear production is realized using high-Z material as the electron-to-photon converter. NorthStar plans not to use a high-Z converter in the initial production target design, but it may be interested in the increased production capabilities a high-Z converter can provide. The purpose of this report is to evaluate the advantages and disadvantages of incorporating a high-Z converter into the target design.

07 ISOTOPE AND RADIATION SOURCES↗

BETO 2021 Peer Review - Biological Upgrading of Sugars (BUS) 2.3.2.105

The Biological Upgrading of Sugars (BUS) project directly targets the anaerobic conversion of lignocellulosic feedstocks into intermediate molecules readily upgradeable to fuel precursors. Recent efforts on the BUS project have a particular emphasis on the biological production of butyric acid, an intermediate that can be readily upgraded to sustainable aviation fuel, diesel blend-stocks, and high value chemicals. The BUS project approaches this direction through a combination of strain engineering, fermentation process engineering, development of novel separations technologies, and the design and build of pilot scale systems. Our ultimate project goal is to develop an integrated cost-effective process at pilot scale to achieve DOE's MYPP targets of $2.50/GGE. The major thrust of the BUS project over the last project cycle was on the development of integrated processes surrounding the anaerobic production of carboxylic acids using diverse Clostridium species. We developed and expanded genetic tools for several Clostridium species and rewired microbial metabolism in an attempt to maximize substrate utilization and flux towards butyric acid. We designed and built novel bioreactors with an in situ product recovery system enabling the biological production and recovery of highly purified acids. We leveraged this system to generate 100s of grams of acid from corn stover hydrolysate. In this presentation we highlight data surrounding our proposed process and accompanying results from technoeconomic and life-cycle analyses of our integrated process. Finally, we detail plans of our pilot scale reactor system that is in process and discuss our future routes towards achieving economically viable and sustainable diesel and jet blendstocks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Grid-Enhanced, Mobility-Integrated Network Infrastructures for Extreme Fast Charging (GEMINI-XFC)

GEMINI-XFC will use first-of-a-kind integrated high-fidelity grid and transport modeling to identify effective pathways for widespread electrification, to design and evaluate integrated vehicle-grid control schemes, and to optimize electric vehicle integration at a full regional scale with individual customer resolution. Control variables will include: Charging station design and planning (where and what kind of charging stations); EV route scheduling considering grid "status"; and Dispatch of behind-the-meter energy storage and legacy voltage control actuators (on-load tap changes, voltage regulators, capacitors).

DIRECT ENERGY CONVERSION,POWER TRANSMISSION AND DI↗

Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) for Transportation Hubs (Final Report)

This report summarizes the work performed under the award number EE0008524. The project develops the Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) platform as the next-generation transportation solution based on autonomous electric vehicles (AEV) serving passenger trips from and to urban transportation hubs, to substantially reduce transportation energy consumption. Extensive data collection and analyses were first conducted to understand the demand patterns and energy consumption of hub-based on-road trips. Then, a data-driven framework that consists of an analytical module and a simulation module was proposed. For the analytical module, five planning + operation tools were developed to support the planning and energy-efficient operations of urban AEV services: the charging station planning that robotically allocates charging supplies based on the stationary charging demand distribution; the transit planning and demand adaptive scheduling model that efficiently generates\ candidate transit routes from hubs to other places and dynamically adjusts the transit time table to fit the current demand; the online energy-efficient routing that learns the energy-optimal paths from observations of link-level energy consumption in real-time; the hub-based ridesharing that matches trip requests together with account for the uncertainty of future trip demand and vehicle supply; and finally, the integrated demand prediction and anomaly detection pipeline that leverages the flight/train time table and support other planning/operation tools. To demonstrate the performance of these tools, a scalable high-performance agent-based simulator was built. We divided the urban space into multiple service zones where each zone was considered as an agent for passenger generation and vehicle charging. Two types of AEV agents were coded to model two types of mobility services: AEV taxi and AEV transit. For the AEV taxi, the team implemented the functions of pickup/drop-off passengers, energy-efficient routing, ridesharing, fleet rebalancing, and recharging. For the AEV bus, the team implemented the functions of demand-adaptive route scheduling, passenger boarding, and recharging. A high-performance computing framework was introduced to receive various profiling information (such as link energy updates, vehicle speed) from the simulator instances and communicate the operational commands back to the instances. The numerical experiments show that each of the proposed operational algorithms can reduce energy consumption and improve system efficiency. Furthermore, there exists the need to collectively consider multiple planning + operational strategies as multiple strategies can influence each other in terms of performance impacts. Recommendations for future work related to AEV planning and simulation are discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Commuter preferences for a first-mile/last-mile microtransit service in the United States

Transportation system models rely heavily upon value of time (VOT) estimates to predict customer behavior. Accurate VOT estimates are particularly vital for planning new services such as on-demand ride hailing or microtransit because customers’ sensitivity to wait time, walk time, and route detour time affects their likelihood of selecting these modes. If an incorrect VOT is assumed during service planning, then ridership will be depressed because of a mismatch between their preferences and how the system is designed. In this paper, we report on the measurement of VOT for microtransit, a shared first-mile/last-mile mobility service, obtained using stated preference microdata from four U.S. cities. Here, we found a median in-vehicle VOT for microtransit of $\$$18.63 (95% CI: $\$$13.39–$\$$24.46) and an access VOT of $\$$75.38 (95% CI: $\$$59.22–$\$$94.96). The former is practically equal to the VOT we found for respondents’ current modes ($\$$20.24, 95% CI: $\$$13.71–$\$$26.94). We also found that men, younger riders, the highly educated, and transit riders are more likely to be interested in microtransit. Since the disutility of time spent on microtransit is not higher than that of other modes, we believe this new service has the potential to attract riders, and particularly if the system is designed with low waiting and walking times.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

U328 Electrical Reliability Project Soil Sampling and Analysis Plan

Lawrence Livermore National Laboratory's (LLNL’s) Project Management Office (PMO) is planning to install an underground electrical duct bank at the 3200 block of the Livermore Site (project). The proposed project will include a new electrical substation and feeders, demolition and replacement of the U328C utility building with a new structure to the west, re-routing of utilities, and update of the parking lot. This Sampling and Analysis Plan (SAP) outlines the procedures to collect and evaluate environmental samples for disposition of the excavated soil during the project and geotechnical samples for pavement design. This SAP has been prepared and is organized to be consistent with LLNL's Soils Screening and Management Plan (SSMP) (LLNL, 2022), as well as the U.S. Environmental Protection Agency's (EPA) Data Quality Objectives (DQO) process (EPA, 2006). In addition to the environmental samples, geotechnical samples will be collected by Consolidated Engineering Laboratories (CEL) on behalf of PMO. Geotechnical samples will be collected from a dedicated geotechnical boring location or co-located with environmental samples. Collection and evaluation of the geotechnical samples is determined by CEL and is therefore not discussed in this SAP.

54 ENVIRONMENTAL SCIENCES↗

Progress in the Verification and Validation Efforts for START: A Spent Fuel Routing Tool

The U.S. Department of Energy’s (DOE) Office of Nuclear Energy (DOE-NE) is planning for an integrated waste management approach to transport, store, and dispose of spent nuclear fuel (SNF) and other high-level radioactive waste (HLW) as part of the Integrated Waste Management (IWM) program [1]. In support of this effort, the Stakeholder Tool for Assessing Radioactive Transportation (START) is being developed within the IWM program [2, 3]. This is a web-based decision support tool that can be used to analyze geospatial data related to the transportation of SNF and HLW. START is designed as a web-based application using an ArcGIS server through which the user can select the origin and destination of the route [4]. This is followed by selection of the mode of transportation of choice based on user preference. Some of the modes available to the user include rail, heavy haul truck, and barge. The option of utilizing more than one mode of transportation (intermodal transportation) is also implemented in START. A few examples of intermodal transportation include barge to rail, and heavy haul truck to rail. It must be noted that some routes might not have access to all modes of transportation, depending on the infrastructure availability at the origin and destination sites. Users can also select any stops or barriers they would like to introduce in the routes. This is followed by selection of the routing criteria of interest. Three primary routing options available to the user include minimum population, minimum distance, and minimum time. Apart from that, a few other options include accounting for a weighted average of the three aforementioned routing options. The next step involves the selection of the buffer distance of interest which includes the two choices available of 800 m and 2500 m, respectively. Finally, an option to select any prohibited rail carriers that the user does not wish to use is available. After making these selections, a route is ready to be created.

Gadey, Harish Reddy↗

Joint Planning of Electricity Transmission and Hydrogen Transportation Networks

The abundance and uneven distribution of renewable energy might cause congestion and curtailment in electric power systems. Transmission expansions can potentially alleviate transmission congestion and reduce renewable energy curtailment. On the other hand, with the substantial cost reduction of electrolyzer technology and the continuing rise of hydrogen demand, converting surplus renewable energy to hydrogen provides synergistic benefits to power and hydrogen systems, but consequently requires joint planning of the two systems. To this end, we propose a joint planning approach for power transmission and hydrogen transportation networks to coordinately optimize the investment and operation of power and hydrogen infrastructure. In our proposed model, detailed truck routing, pipeline, and hydrogen storage are formulated to quantify the flexibility of hydrogen transportation system. A robust joint planning approach is also proposed to address various uncertainties from renewable energy, electric load, and hydrogen demand. Furthermore, our numerical simulations show that the proposed joint planning model can save the total system cost, reduce renewable energy curtailment, and increase the utilization level of transmission lines.

08 HYDROGEN↗

Time-Constrained Capacitated Vehicle Routing Problem in Urban E-Commerce Delivery

Electric vehicle routing problems can be particularly complex when recharging must be performed mid-route. In some applications, such as e-commerce parcel delivery truck routing, however, mid-route recharging may not be necessary because of constraints on vehicle capacities and the maximum allowed time for delivery. In this study, we develop a mixed-integer optimization model that exactly solves such a time-constrained capacitated vehicle routing problem, especially of interest for e-commerce parcel delivery vehicles. We compare our solution method with an existing metaheuristic and carry out exhaustive case studies considering four U.S. cities—Austin, TX; Bloomington, IL; Chicago, IL; and Detroit, MI—and two vehicle types: conventional vehicles and battery electric vehicles (BEVs). In these studies we examine the impact of vehicle capacity, maximum allowed travel time, service time (dwelling time to physically deliver the parcel), and BEV range on system-level performance metrics, including vehicle miles traveled (VMT). We find that the service time followed by the vehicle capacity plays a key role in the performance of our approach. We assume an 80-mi BEV range as a baseline without mid-route recharging. Our results show that the BEV range has a minimal impact on performance metrics because the VMT per vehicle averages around 72 mi. In a case study for shared-economy parcel deliveries, we observe that VMT could be reduced by 38.8% in Austin if service providers were to operate their distribution centers jointly.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Joint optimal scheduling for electric vehicle battery swapping-charging system based on wind farms

Insufficiencies in charging facilities limit the broad application of electric vehicles (EVs). In addition, EV can hardly represent a green option if its electricity primarily depends on fossil energy. Considering these two problems, this paper studies a battery swapping-charging system based on wind farms (hereinafter referred to as W-BSCS). In a W-BSCS, the wind farms not only supply electricity to the power grid but also cooperate with a centralized charge station (CCS), which can centrally charge EV batteries and then distribute them to multiple battery swapping stations (BSSs). The operational framework of the W-BSCS is analyzed, and some preprocessing technologies are developed to reduce complexity in modeling. Then, a joint optimal scheduling model involving a wind power generation plan, battery swapping demand, battery charging and discharging, and a vehicle routing problem (VRP) is established. Then a heuristic method based on the exhaustive search and the Genetic Algorithm is employed to solve the formulated NP-hard problem. Numerical results verify the effectiveness of the joint optimal scheduling model, and they also show that the W-BSCS has great potential to promote EVs and wind power.

17 WIND ENERGY↗