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DOE OSTI2024

Homomorphic Encryption for Electrical Metering Aggregation: Protecting the Privacy of Building Tenants

Electrical meters are devices that measure consumer electricity usage. The data collected by these meters is necessary for utility billing and electrical grid management but can also be used to assess the environmental impact of buildings. Prior research has found that unprotected metering data could potentially be used to infer some information about the behaviors of building tenants by detecting changes in electricity usage. For example, a period of low electricity usage could suggest that the tenants are not in the building. As smart metering becomes more common, there is a growing need for data privacy protections for metering data that do not negatively impact the quality and availability of data used for energy management and billing applications. To identify potential solutions, we developed a Python-based data aggregation platform to analyze the potential efficacy of privacy-enhancing technologies for energy metering applications. This platform aggregates groups of metering sites into virtual buildings, which could potentially detach changes in electrical activity from individual tenants, making it more difficult to track the activity of a specific tenant. To further protect data during analysis, this project utilizes homomorphic encryption as part of its initial approach. Homomorphic encryption offers a means of protecting energy consumption data while permitting mathematical operations to be performed without the need to know the data contents. This allows for data to be processed into usable statistics without revealing energy consumption information. A series of homomorphic encryption libraries were evaluated to determine their applicability and limitations in the context of metering data. The use of these techniques may help to reassure consumers and encourage further adoption of smart grid infrastructure.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Feasibility Analysis of Taxi Fleet Electrification Using 4.9 Million Miles of Real-World Driving Data: Preprint

Ride hailing activity is rapidly increasing, largely due to the growth of transportation network companies such as Uber and Lyft. However, traditional taxi companies continue to represent an important mobility option for travelers. Columbus Yellow Cab, a taxi company in Columbus, Ohio, offers traditional line-of-sight hailing as well as digital hailing through a mobile app. Data from Columbus Yellow Cab was provided to the National Renewable Energy Laboratory to analyze the potential for taxi electrification. Columbus Yellow Cab data contained information describing both global positioning system trajectories and taxi meter information. The data spanned a period of 13 months, containing approximately 70 million global system positioning system points, 840 thousand trips, and 170 unique vehicles. A variety of scenarios were evaluated using Columbus Yellow Cab data and the Electric Vehicle Infrastructure Projection Tool (EVI-Pro) to understand challenges and opportunities associated with operating an electrified taxi fleet. Two main factors-access to home charging and vehicle specifications-are shown to be major variables affecting successful electric fleet operation. The analysis indicates that 95.7% of taxi travel days can be successfully completed by a 250-mile-range electric vehicle assuming access to overnight and public charging infrastructure. However, when no overnight access is available to fleet vehicles, only 39.9% of taxi travel days are possible with 250-mile range electric vehicles. An additional scenario, reducing the vehicle range from 250 miles to 100 miles (while controlling for infrastructure access and permitting overnight charging) resulted in only 34.4% of taxi travel days being completed.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Electrifying Road Trips to and from National Parks in the Western United States

We evaluate charging infrastructure requirement for electrified long-distance travels to/from national parks in the Western U.S. We conduct a high-resolution spatial and temporal analysis of road trips in the region, accounting for detailed travel volume and pattern, the type of electric vehicles, heterogeneous energy consumption rates depending on driving conditions, charging technology (e.g., power and speed), and charging behavior. The scope includes on-route (or way-point) charging as well as destination charging (in national parks). We estimate the locations and sizes of required charging stations in the entire Western U.S. to enable electrified road trips to/from national parks. We also examine environmental justice and energy equity aspects of projected charging infrastructure (for national parks) in the context of the overall vehicle electrification and charging infrastructure build-out.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

DOE OSTI2014

Road ecology in environmental impact assessment

Transport infrastructure has a wide array of effects on terrestrial and aquatic ecosystems, and road and railway networks are increasingly being associated with a loss of biodiversity worldwide. Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA) are two legal frameworks that concern physical planning, with the potential to identify, predict, mitigate and/or compensate transport infrastructure effects with negative impacts on biodiversity. The aim of this study was to review the treatment of ecological impacts in environmental assessment of transport infrastructure plans and projects. A literature review on the topic of EIA, SEA, biodiversity and transport infrastructure was conducted, and 17 problem categories on the treatment of biodiversity were formulated by means of a content analysis. A review of environmental impact statements and environmental reports (EIS/ER) produced between 2005 and 2013 in Sweden and the UK was then conducted using the list of problems as a checklist. The results show that the treatment of ecological impacts has improved substantially over the years, but that some impacts remain problematic; the treatment of fragmentation, the absence of quantitative analysis and that the impact assessment study area was in general delimited without consideration for the scales of ecological processes. Actions to improve the treatment of ecological impacts could include improved guidelines for spatial and temporal delimitation, and the establishment of a quantitative framework including tools, methods and threshold values. Additionally, capacity building and further method development of EIA and SEA friendly spatial ecological models can aid in clarifying the costs as well as the benefits in development/biodiversity tradeoffs. - Highlights: • The treatment of ecological impacts in EIA and SEA has improved. • Quantitative methods for ecological impact assessment were rarely used • Fragmentation effects were recognized but not analysed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Accelerating Science Impact through Big Data Workflow Management and Supercomputing

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. ATLAS, one of the largest collaborations ever assembled in the the history of science, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. To manage the workflow for all data processing on hundreds of data centers the PanDA (Production and Distributed Analysis)Workload Management System is used. An ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF), is realizing within BigPanDA and megaPanDA projects. These projects are now exploring how PanDA might be used for managing computing jobs that run on supercomputers including OLCF’s Titan and NRC-KI HPC2. The main idea is to reuse, as much as possible, existing components of the PanDA system that are already deployed on the LHC Grid for analysis of physics data. The next generation of PanDA will allow many data-intensive sciences employing a variety of computing platforms to benefit from ATLAS experience and proven tools in highly scalable processing.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Expanding the Photovoltaic Supply Chain in the United States: Opportunities and Challenges

Growth in U.S. manufacturing of solar-grade polysilicon, photovoltaic (PV) cells, and PV modules has not kept pace with global growth in these industries, and in some cases has even decreased. As a result, the United States has lost approximately 80% of its global market share in these industries over the past decade. However, projections of strong PV demand growth continuing in the United States and globally—along with significant announced U.S. cell and module plant expansions—suggest that PV could have important near-term impacts on related U.S. manufacturing sectors. This report primarily considers the infrastructure availability in the United States to meet demand for industries upstream of PV manufacturing if all U.S. PV installations were manufactured domestically from domestically sourced materials and components. It does not evaluate economic factors such as cost-competitiveness with other countries, policy incentives, shipping costs, and so forth, which are important factors to evaluate but are outside the scope of this work. Our goal is to delineate the infrastructure challenges and opportunities that upstream U.S. manufacturing sectors could encounter if the U.S. PV manufacturing sector grows. This analysis could be used in future discussions of the feasibility of creating a domestic PV supply chain that relies on domestic sourcing for upstream materials.

14 SOLAR ENERGY↗

DOE OSTI2020

Electrification Futures Study: Methodological Approaches for Assessing Long-Term Power System Impacts of End-Use Electrification

By its nature, electrification enhances the coupling between the electric sector and end-use sectors. Assessing the impacts of electrification requires both an examination of the complex interactions between sectors and a broader assessment of multiple parts of the energy system. The Electrification Futures Study (EFS) uses several complementary modeling and analysis tools to analyze the impacts of electrification on the U.S. energy system. In particular, the EFS relies on an overarching scenario analysis approach, but through the use of separate modeling approaches designed to assess various electricity demand- and supply-side futures. The primary model employed to generate the supply-side scenarios is the Regional Energy Deployment System (ReEDS) model, which is a capacity expansion model for the U.S. electricity system through 2050. Traditionally, the model has been primarily exercised in scenario analysis that implicitly assumed limited electrification. Because of this assumption, resulting future load profiles are approximated by historical ones, load growth is driven primarily by population and economic growth only, and changes in direct end-use natural gas consumption do not effect natural gas costs for electricity generation. In this report, we (1) reflect the potential for resource sharing between regions given these changes in demand, (2) represent how changes in natural gas consumption in end-use sectors could impact the economics of natural gas-fired generation, and (3) document a new model representation of demand-side flexibility used for the EFS. These improvements to ReEDS are employed for the EFS supply-wide analysis, which is summarized in a companion EFS report titled Electrification Futures Study: Scenarios of Power System Evolution and Infrastructure Development for the United States (Murphy et al. 2019). The data and methods documented in this report could also be adapted for other models with similar scope and limitations as ReEDS, and these data and methods could be used to assess future electric system scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRSDate not supplied

Leveraging the 2024 Solar Eclipse to Enhance Science Learning through Citizen Science

The solar eclipse on April 8, 2024, provided a rare and compelling opportunity for educators and students to engage in hands-on citizen science. Two NASA Science Activation projects GLOBE Mission Earth (GME) and NASA Earth Science Education Collaborative (NESEC) partnered together to provide a unique professional development experience for educators interested in the eclipse. They invited educators to participate in a specialized 5-week online workshop designed to engage the educators in Global Learning and Observations to Benefit the Environment (GLOBE) citizen science about the eclipse. The workshop was designed to support their certification as GLOBE educators and develop their knowledge, skills, and confidence in conducting a GLOBE investigation. Over 60 educators from across the United States took part in this workshop, which focused on investigating the eclipse by collecting and analyzing atmospheric data. The GLOBE Program promotes environmental and scientific literacy by enabling participants to collect Earth science data and contribute it to a global database accessible for research. The 2024 GLOBE Eclipse workshop trained educators in specific GLOBE protocols—Clouds, Air Temperature, and Surface Temperature—using the GLOBE Eclipse tool integrated into the GLOBE Observer app. This training was supplemented with guidance on engaging students in authentic scientific research and creating research posters to present their findings. The workshop aimed to enhance educators’ skills and confidence in integrating GLOBE protocols into their teaching practices. It addressed several key areas outlined in the National Academies' report on Learning through Citizen Science, including scientific context, nature of participation, and project infrastructure. Educators learned about the atmospheric effects of solar eclipses and were trained to use scientific tools and data analysis methods relevant to their research. They also engaged in live sessions and asynchronous activities, practicing data collection and analysis with real-time feedback. Survey results from the workshop highlighted that participants were primarily motivated by the desire to better use data in their classrooms and improve their proficiency with the GLOBE Observer app. Post-workshop evaluations showed significant increases in educators' confidence regarding their ability to conduct and guide scientific research. Participants reported feeling well-prepared to use the GLOBE Observer app for data collection and were successful in integrating their eclipse observations into classroom activities. Participants also valued the opportunity to contribute to authentic science through GLOBE, which involved observing atmospheric changes such as air temperature fluctuations and cloud cover alterations during the eclipse. The success of the workshop is evident in the increased confidence and skill levels of educators, as well as the publication of research posters on the GLOBE Mission Earth Student Research webpage.This session will discuss how the GLOBE Eclipse workshop series effectively utilized the unique context of the solar eclipse to enhance science education through citizen science. By adhering to the principles outlined in the Learning through Citizen Science framework, the workshop successfully engaged educators and students in meaningful scientific practices, demonstrating the potential of citizen science to enrich science education and foster a deeper understanding of Earth systems.

Jessica Taylor↗

DOE OSTI2025

HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency

Many workflows in high-energy-physics (HEP) stand to benefit from recent advances in transformer-based large language models (LLMs). While early applications of LLMs focused on text generation and code completion, modern LLMs now support orchestrated agency: the coordinated execution of complex, multi-step tasks through tool use, structured context, and iterative reasoning. We introduce the HEP Toolkit for Agentic Planning, Orchestration, and Deployment (HEPTAPOD), an orchestration framework designed to bring this emerging paradigm to HEP pipelines. The framework enables LLMs to interface with domain-specific tools, construct and manage simulation workflows, and assist in common utility and data analysis tasks through schema-validated operations and run-card-driven configuration. To demonstrate these capabilities, we consider a representative Beyond the Standard Model (BSM) Monte Carlo validation pipeline that spans model generation, event simulation, and downstream analysis within a unified, reproducible workflow. HEPTAPOD provides a structured and auditable layer between human researchers, LLMs, and computational infrastructure, establishing a foundation for transparent, human-in-the-loop systems.

Menzo, Tony [Alabama U.; Fermilab] (ORCID:00000002↗

NASA NTRS2013

Practical Application of PRA as an Integrated Design Tool for Space Systems

This paper presents the application of the first comprehensive Probabilistic Risk Assessment (PRA) during the design phase of a joint NASA/NOAA weather satellite program, Geostationary Operational Environmental Satellite Series R (GOES-R). GOES-R is the next generation weather satellite primarily to help understand the weather and help save human lives. PRA has been used at NASA for Human Space Flight for many years. PRA was initially adopted and implemented in the operational phase of manned space flight programs and more recently for the next generation human space systems. Since its first use at NASA, PRA has become recognized throughout the Agency as a method of assessing complex mission risks as part of an overall approach to assuring safety and mission success throughout project lifecycles. PRA is now included as a requirement during the design phase of both NASA next generation manned space vehicles as well as for high priority robotic missions. The influence of PRA on GOES-R design and operation concepts are discussed in detail. The GOES-R PRA is unique at NASA for its early implementation. It also represents a pioneering effort to integrate risks from both Spacecraft (SC) and Ground Segment (GS) to fully assess the probability of achieving mission objectives. PRA analysts were actively involved in system engineering and design engineering to ensure that a comprehensive set of technical risks were correctly identified and properly understood from a design and operations perspective. The analysis included an assessment of SC hardware and software, SC fault management system, GS hardware and software, common cause failures, human error, natural hazards, solar weather and infrastructure (such as network and telecommunications failures, fire). PRA findings directly resulted in design changes to reduce SC risk from micro-meteoroids. PRA results also led to design changes in several SC subsystems, e.g. propulsion, guidance, navigation and control (GNC), communications, mechanisms, and command and data handling (C&DH). The fault tree approach assisted in the development of the fault management system design. Human error analysis, which examined human response to failure, indicated areas where automation could reduce the overall probability of gaps in operation by half. In addition, the PRA brought to light many potential root causes of system disruptions, including earthquakes, inclement weather, solar storms, blackouts and other extreme conditions not considered in the typical reliability and availability analyses. Ultimately the PRA served to identify potential failures that, when mitigated, resulted in a more robust design, as well as to influence the program's concept of operations. The early and active integration of PRA with system and design engineering provided a well-managed approach for risk assessment that increased reliability and availability, optimized lifecyc1e costs, and unified the SC and GS developments.

Kalia, Prince↗

DOE OSTI2026

Latency Analysis of the Nexus Digital Twin Framework

Real-time digital catalogs are increasingly relied upon to track metadata and connect disparate data sources for cloud-based data integration efforts. One such tool, Deeplynx Nexus is supporting real-time digital twin efforts through event-driven data integration and time-series queries. Nexus’s usefulness for these applications depends critically on how quickly individual records can be uploaded and downloaded, since delays directly affect the responsiveness of any system built on top of it. However, the actual latency a user should expect from Nexus has not been systematically measured before, particularly for the small, frequent transactions typical of live sensor feeds. Here we show that single-record round-trip latency is 61.1 ms on a local Nexus instance and 391.7 ms on the hosted production infrastructure, a roughly 6.4x difference driven primarily by fixed per-request overhead rather than data volume. This overhead dominates at small scale: comparing single-record and ten-record trials suggests approximately 56 ms of each single-record request is fixed connection and authentication cost rather than data-transfer time, meaning batching even a handful of records is substantially more efficient than transmitting them individually. At large batch sizes, this pattern reverses for uploads, which converge to near parity between local and hosted environments by 25,000-50,000 records, while download latency remains persistently 5.7-6.4x slower on hosted infrastructure even at scale. These results suggest that Nexus deployments intended for real-time digital twin applications should prioritize record batching over single-record transactions, and that download-path optimization on hosted infrastructure offers the largest remaining opportunity to reduce latency at scale. We anticipate these baseline measurements will serve as a reference point for future digital twin projects evaluating whether Nexus’s latency profile meets their real-time requirements, and as a benchmark for tracking the effect of future infrastructure or API changes.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Exploring the Potential of Second-Life Batteries for Mobile Charging Infrastructure: A Review

This review paper investigates the potential applications of second-life batteries (SLBs) specifically for mobile charging stations. As the adoption of electric vehicles (EVs) continues to rise, the need for accessible and efficient charging infrastructure becomes increasingly critical to address range anxiety of EV owners. The repurposing of SLBs presents a promising solution to address this need, offering cost-effective and sustainable alternatives to traditional stationary charging infrastructure. This paper examines key technical considerations, including battery chemistry, state of health assessment, heterogeneity and battery management system design, and safety protocols tailored to SLBs. The paper also highlights economic and environmental implications of utilizing SLBs in mobile charging applications, encompassing techno-economic analysis techniques and sustainability metrics. Through an exploration of challenges, opportunities, and emerging trends, this review aims to provide valuable insights to stakeholders involved in the development and deployment of SLBs in mobile charging infrastructure.

Gautam, Mukesh (ORCID:0000000305715825)↗

DOE OSTI2023

Building an Efficient Cluster Cosmology Software Package for Modeling Cluster Counts and Lensing

We introduce a software suite developed for galaxy cluster cosmological analysis with the Dark Energy Survey Data. Cosmological analyses based on galaxy cluster number counts and weak-lensing measurements need efficient software infrastructure to explore an increasingly large parameter space, and account for various cosmological and astrophysical effects. Our software package is designed to model the cluster observables in a wide-field optical survey, including galaxy cluster counts, their averaged weak-lensing masses, or the cluster's averaged weak-lensing radial signals. To ensure maximum efficiency, this software package is developed in C++ in the CosmoSIS software framework, making use of the CUBA integration library. We also implement a testing and validation scheme to ensure the quality of the package. We demonstrate the effectiveness of this development by applying the software to the Dark Energy Survey Year 1 galaxy cluster cosmological data sets, and acquired cosmological constraints that are consistent with the fiducial Dark Energy Survey analysis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Adapting Traditional Hazards Analysis Methods to Address Cyber Risks

Traditional hazards analysis (HA) methods, originally developed to address physical and operational risks, often fall short when it comes to identifying and mitigating cyber threats. These cyber threats pose unique and evolving risks to critical infrastructure and industrial control systems (ICS). This report explores the integration of Cyber-Informed Engineering (CIE) principles into existing HA methods to enhance their ability to address cyber-induced risks. CIE provides organizations with a practical, cost-effective approach to closing the gap between traditional HA methods and the need for cyber risk mitigation. By leveraging existing safety processes and controls, CIE allows users to examine and mitigate cyber vulnerabilities without overhauling existing HA methods. This report identifies areas where HA and CIE naturally align and where their approaches diverge. It emphasizes how CIE principles can be used to adapt HA methods, broadening their scope to include cyber risks and enabling the mitigation of cyber- induced impacts alongside traditional hazards and failure scenarios. This report examines how CIE can be applied across various HA methods—such as Hazard and Operability Studies (HAZOP), Probabilistic Risk Assessment (PRA), Failure Modes and Effects Analysis (FMEA), Systems-Theoretic Process Analysis (STPA), Hazard and Consequence Analysis for Digital Systems (HAZCADS), and Layers of Protection Analysis (LOPA). It provides strategies for integrating CIE to strengthen the identification, assessment, and mitigation of cyber-induced risks. The findings offer a structured entry point for organizations to embed CIE concepts into hazards and safety analyses, as well as broader engineering processes, ultimately supporting the design and operation of a more resilient infrastructure.

42 ENGINEERING↗

NASA NTRS2006

A Case for Developing a Ground Based Replication of the Earth, Moon and Mars Spaceflight Infrastructure

When the systems are developed and in place to provide the services needed to operate en route and on the Lunar and Martian surfaces, an Earth based replication will need to be in place for the safety and protection of mission success. The replication will entail all aspects of the flight configuration end to end but will not include any closed loop systems. This would replicate the infrastructure from Lunar and Martian robots, manned surface excursions, through man and unmanned terrestrial bases, through the various types of communication systems and technologies, manned and un-manned space vehicles (large and small), to Earth based systems and control centers. An Earth based replicated infrastructure will enable checkout and test of new technologies, hardware, software updates and upgrades and procedures without putting humans and missions at risk. Analysis of events, what ifs and trouble resolution could be played out on the ground to remove as much risk as possible from any type of proposed change to flight operational systems. With adequate detail, it is possible that failures could be predicted with a high probability and action taken to eliminate failures. A major factor in any mission to the Moon and to Mars is the complexity of systems, interfaces, processes, their limitations, associated risks and the factor of the unknown including the development by many contractors and NASA centers. The need to be able to introduce new technologies over the life of the program requires an end to end test bed to analyze and evaluate these technologies and what will happen when they are introduced into the flight system. The ability to analyze system behaviors end to end under varying conditions would enhance safety e.g. fault tolerances. This analysis along with the ability to mine data from the development environment (e.g. test data), flight ops and modeling/simulations data would provide a level of information not currently available to operations and astronauts. In this paper we will analyze the beginnings of such a replication and what it could do in terms of reducing risk in the near term for development. We will analyze the Space Shuttle Main Engine (SSME) test lab which has to a large extent accomplished this replication for the SSME and has been highly successful in analyzing hardware and software problems and changes. The cost of replicating the flight system as proposed here could be very high if attempted as an afterthought. We will describe the initial steps for the development of a replication of this infrastructure starting with the communication infrastructure. The Constellation of Labs (CofL) under the Command, Control, Communication and Information (C3I) project for the NASA Exploration Initiative will provide the initial foundation upon which to base this replication. Simply put, there is very little margin for error in high latency situations e.g. en-route to/from Mars or in an autonomous process on the Lunar far side. Any thought out approach to reduce risk and increase safety needs to be accomplished end to end with the actual systems configuration.

Bradford, Robert N.↗

DOE OSTI2025

Adapting Traditional Hazards Analysis Methods to Address Cyber Risks

42 - ENGINEERING↗

DOE OSTI2025

Physics-Based Analysis of Cell Imbalances and Aging in Lithium-Ion Battery Modules and Packs

Lithium-ion battery (LIB) packs are a key solution for grid-scale energy storage, enabling grid resilience and supporting critical infrastructure. LIB modules and packs experience current imbalances and uneven cell aging due to various design and operational factors, and require a battery management system (BMS) to continuously monitor and control. In this context, a physics-based modeling framework for LIB modules and packs (liionpack) was enhanced to identify design and control strategies that minimize current imbalance and improve module/pack operation. Simulations of an 8-cell parallel-connected module demonstrate that reducing current imbalance leads to more uniform cell aging and improved module/pack-level degradation predictions. The analysis shows that current imbalance are affected by the electrical resistances. Terminal location significantly affects imbalance, with opposite-end terminal connections at intermediate branches minimizing the imbalance, and the pack circuit construction influences the accuracy of physics-based analysis at the pack scale. This framework enables design optimization of modules and packs through a fast and easy evaluation of pack performance and aging, and supports the development of aging-informed balancing strategies compatible with BMS implementation. Thereby, offering practical pathways to improve reliability and cycle life predictions in large-scale battery energy storage systems.

Ayalasomayajula, Surya Mitra [Oak Ridge National L↗

DOE OSTI2020

Thermal Analysis of Wireless Power Transfer Coils for Dynamic Wireless Electric Vehicle Charging

In this paper, safe operating conditions of a wireless power transfer coil were identified and road infrastructure for a dynamic wireless electric vehicle charging system was studied. Magneto-thermal simulations were used to map the power loss directly into the computed fluid dynamics solver. This method allowed the authors to analyze the heating pattern of the enclosed wireless power transfer coil in the road structure, as well as for the vehicle coil. Thermal heating patterns for three types of rectangular coil structures were analyzed. Heating patterns were analyzed for 200 kW coils and different magnetic field densities in the magnetic core.

Wojda, Rafal↗