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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 541 records · Page 30

Degradation of a Cr-Mo steel by carbide precipitation over long-term service

Microstructure of the 40-year service-exposed 1Cr-0.5Mo steel extracted from pressure vessels through the boat sampling technique was characterized using x-ray diffraction, field-emission scanning electron microscopy, energy dispersive spectrometry, electron backscatter diffraction, focused ion beam, and transmission electron microscopy. The microstructure degradation during long-term service was identified. Statistical crystal plastic ity models were developed to correlate the microstructure and mechanical properties quantitatively. The steel is found significantly strengthened but slightly embrittled. Nanoscale Mo 2 C carbides have nucleated within the ferrite matrix over the long-term service, resulting in significant strengthening of the matrix. The coarser grain boundary Cr 23 C 6 carbides, on the other hand, act as the damage accumulation sites and lead to the degradation.

36 MATERIALS SCIENCE↗

Automating ridehailing services would reduce pooling, especially among women

Here, this study investigates how autonomous vehicles (AVs) could transform pooled (shared) ridehailing services, focusing on the impacts of fare reductions, the absence of drivers/staff, and psychological attributes such as trust in other passengers and privacy concerns. We distinguish between the automation of driving tasks and the removal of human driver/staff from the vehicle, providing novel insights into the factors influencing AV ridehailing adoption. Using a national survey with stated preference (SP) choice experiments and psychometric questions, we analyze the complex interactions of ridehailing fare, pooled ridehailing service quality, and latent attitudes on ridehailing choices. Our findings suggest that the elimination of drivers/staff from fully autonomous ridehailing could lead to a shift from pooled to solo rides, particularly among female travelers who may have greater concerns about trust and safety in unstaffed AVs. This study highlights the importance of addressing trust and comfort beyond fare discounts to ensure the inclusivity and widespread adoption of pooled AV ridehailing. These insights underscore the need for ridehailing providers and policymakers to prioritize trust-building measures, user-centered AV design that offers greater privacy, and dynamic pricing strategies, to ensure inclusive and widespread adoption of pooled AV services.

Autonomous vehicle↗

Towards an Intelligent Data Delivery Service

The ATLAS Event Streaming Service (ESS) at the LHC is an approach to preprocess and deliver data for Event Service (ES) that has implemented a fine-grained approach for ATLAS event processing. The ESS allows one to asynchronously deliver only the input events required by ES processing, with the aim to decrease data traffic over WAN and improve overall data processing throughput. A prototype of ESS was developed to deliver streaming events to fine-grained ES jobs. Based on it, an intelligent Data Delivery Service (iDDS) is under development to decouple the "cold format" and the processing format of the data, which also opens the opportunity to include the production systems of other HEP experiments. Here we will at first present the ESS model view and its motivations for iDDS system. Then we will also present the iDDS schema, architecture and the applications of iDDS.

97 MATHEMATICS AND COMPUTING↗

Automated Network Services for Exascale Data Movement

The Large Hadron Collider (LHC) experiments distribute data by leveraging a diverse array of National Research and Education Networks (NRENs), where experiment data management systems treat networks as a “blackbox” resource. After the High Luminosity upgrade, the Compact Muon Solenoid (CMS) experiment alone will produce roughly 0.5 exabytes of data per year. NREN Networks are a critical part of the success of CMS and other LHC experiments. However, during data movement, NRENs are unaware of data priorities, importance, or need for quality of service, and this poses a challenge for operators to coordinate the movement of data and have predictable data flows across multi-domain networks. The overarching goal of SENSE (The Software-defined network for End-to-end Networked Science at Exascale) is to enable National Labs and universities to request and provision end-to-end intelligent network services for their application workflows leveraging SDN (Software-Defined Networking) capabilities. This work aims to allow LHC Experiments and Rucio, the data management software used by CMS Experiment, to allocate and prioritize certain data transfers over the wide area network. In this paper, we will present the current progress of the integration of SENSE, Multi-domain end-to-end SDN Orchestration with QoS (Quality of Service) capabilities, with Rucio, the data management software used by CMS Experiment.

Balcas, Justas↗

Automated Electric Vehicle Fleet Operations for On-Demand Service: Challenges and Opportunities

Automated/autonomous vehicle fleet operations within automated mobility districts have been studied over the past five years by the National Renewable Energy Laboratory, a US Department of Energy federally funded research and development center. This paper extends the analysis in this third phase of research underway to include considerations for electric vehicle operations and charging within a fleet of right-sized automated vehicles providing on-demand public mobility services. The current focus of research is on the operational complexities and associated challenges for automated/autonomous vehicles employing electric drivetrains and the resultant need for an efficient battery charging process while vehicles are operating in an "on-demand" mode of service. The blossoming of microtransit with shared-ride and point-to-point dispatching of each vehicle instills complex operations, with multiple mobility-on-demand transit operating sites being deployed, studied, and analyzed across North America. As a starting point, the authors' experience over the past 20 years with the analysis of automated transit network systems operating on and within dedicated and protected transitways provides initial insights into the system-level operational implications for maintaining a sufficient battery charge for a fleet of automated vehicles. Lessons learned through the prior analyses of automated transit network systems operating in on-demand service are identified, along with the capital cost implications for the requisite operating fleet size and charging station infrastructure for various approaches. These costs are summarized in juxtaposition with the benefits of realizing the higher goals of reducing environmental impacts and energy use within automated mobility districts as automated/autonomous vehicle technology matures. Finally, the discussion addresses key aspects of battery-electric propulsion for managed fleets in fully automated operation that will be studied as the third phase of research continues.

ADVANCED PROPULSION SYSTEMS↗

An Optimization-Based Planning Tool for On-Demand Mobility Service Operations

Regions worldwide are adopting and exploring low-speed automated electric shuttle (AES) service as an on-demand shared mobility service in dense geofenced urban areas. Building on this concept, the National Renewable Energy Laboratory (NREL) recently developed the Automated Mobility District (AMD) toolkit. The AMD toolkit—comprising of a travel micro-simulation model and an energy estimation model—estimates the mobility and energy impacts of a given shuttle configuration within an AMD. Early-stage AMD deployments need to find optimal operational configurations that include: (a) passenger capacity of an AES, (b) time-dependent routes, and (c) fleet size (AES units) to satisfy the demand for the region. This research extends the AMD toolkit functionality by developing an optimization-based planning module that will assist in the operations of AES units. We developed a constrained mixed-integer program accounting for passenger waiting time, battery range, and passenger capacity of AES units. For scalability, we demonstrated the Tabu search-based solution technique for a real-world network—a proposed AMD deployment in Greenville, South Carolina, USA. Compared to rule-based operations, our developed solution yields higher travel time and energy savings for the network at different demand levels. The sensitivity analyses for waiting time thresholds indicate nonlinearity in the system performance, underscoring the need to meet shared-use mobility user-level expectations. The developed optimization framework can be adapted and extended to accommodate different categories of shared-use on-demand mobility services.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Pufferscale: Rescaling HPC Data Services for High Energy Physics Applications

User-space HPC data services are emerging as an appealing alternative to traditional parallel file systems, because of their ability to be tailored to application needs while eliminating unnecessary overheads incurred by POSIX compliance. The High Energy Physics (HEP) community is progressively turning towards such services to enable high-throughput accesses under heavy concurrency to billions of event data produced by instruments and consumed by subsequent analysis workflows. Such services would benefit from the possibility to be rescaled up and down to adapt to changing workloads, as experimental campaigns progress, in order to optimize resource usage. This paper formalizes rescaling a distributed storage system as a multi objective optimization problem considering three criteria: load balance, data balance, and duration of the rescaling operation. We propose a heuristic for rapidly finding a good approximate solution, while allowing users to weight the criteria as needed. The heuristic is evaluated with Pufferscale, a new rescaling manager for microservice-based distributed storage systems. To validate our approach in a real-world ecosystem, we showcase the use of Pufferscale as a means to enable storage malleability in the HEPnOS storage system for HEP applications.

Distributed Storage System↗

A Framework for Self-Adaptive Dispersal of Computing Services

Modern networking architectures are making it increasingly possible to disperse services not just across servers but into intermediate network devices as well. Here we introduce the Misson-oriented Adaptive Placement (MAP) architecture, which synthesizes prior work on middleware, load-balancing, constraint solving, and aggregate programming into a framework for self-adaptive management of dispersed services. We provide a first evaluation of the efficacy and resilience that can be provided through this approach: results in simulation demonstrating that MAP can autonomously change the deployment of services to adapt to changing needs and failures.

Paulos, Aaron↗

An Online Approach to Solve the Dynamic Vehicle Routing Problem with Stochastic Trip Requests for Paratransit Services

Many transit agencies operating paratransit and microtransit services have to respond to trip requests that arrive in real-time, which entails solving hard combinatorial and sequential decision-making problems under uncertainty. To avoid decisions that lead to significant inefficiency in the long term, vehicles should be allocated to requests by optimizing a non-myopic utility function or by batching requests together and optimizing a myopic utility function. While the former approach is typically offline, the latter can be performed online. We point out two major issues with such approaches when applied to paratransit services in practice. First, it is difficult to batch paratransit requests together as they are temporally sparse. Second, the environment in which transit agencies operate changes dynamically (e.g., traffic conditions can change over time), causing the estimates that are learned offline to become stale. To address these challenges, we propose a fully online approach to solve the dynamic vehicle routing problem (DVRP) with time windows and stochastic trip requests that is robust to changing environmental dynamics by construction. We focus on scenarios where requests are relatively sparse—our problem is motivated by applications to paratransit services. We formulate DVRP as a Markov decision process and use Monte Carlo tree search to evaluate actions for any given state. Accounting for stochastic requests while optimizing a non-myopic utility function is computationally challenging; indeed, the action space for such a problem is intractably large in practice. To tackle the large action space, we leverage the structure of the problem to design heuristics that can sample promising actions for the tree search. Our experiments using real-world data from our partner agency show that the proposed approach outperforms existing state-of-the-art approaches both in terms of performance and robustness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

ROBIN (RuciO/BIgData Express/SENSE) A Next-Generation High-Performance Data Service Platform

Increasingly, scientific research discoverydepends on the analysis of extremely large amounts of data. Thisdata is gathered through very large scientific instruments, verylarge numbers of small devices, and mid-scale instruments.These devices generate exponentially increasing volumes of data.Such data is often obtained, analyzed, stored, visualized, andtransferred at and among sites world-wide by largecollaborations of science communities. Managing and movingextremely large volumes of data across today’s networks is aspecial multidimensional challenge. Also, existing datamanagement and movement services and tools often areinadequate to address all specific requirements. This paperdescribes the various components of this challenge and howthose issues can be addressed by ROBIN, a uniquecomprehensive set of integrated services designed specificallyfor managing and moving extremely large amounts of data overlong distances, e.g., thousands of miles around the globe. Thispaper also describes the results of initial experiments using thatset of integrated services.

Wu, Wenji↗

Exploring Demographic Factors Behind the User Preferences in Ridesharing Services

Ridesharing is an increasingly prevalent form of transportation. Personal and pooled rideshare services are the two modes of ridesharing available on the market. While personal rideshare features higher time efficiency and better service experience, especially in terms of privacy, pooled rideshare has better energy efficiency and can reduce traffic congestion. To encourage users to utilize pooled rideshare, it is crucial to understand the factors behind preferences between pooled and personal rideshare services. This study conducted a survey study on a sample of 2,884 participants from the U.S. The stated-choice method was employed to collect the usage rate of pooled rideshare in designed scenarios. A detailed analysis of pooled rideshare usage rates among participants from different demographic backgrounds was performed. The results demonstrated demographic factors related to variations in pooled rideshare usage rates. Findings from this study explore the impacts of demographic factors on people's choices in ridesharing and provide important information for the modeling and optimization of ridesharing transportation systems.

Su, Haotian↗

XaaS: Acceleration as a Service to Enable Productive High-Performance Cloud Computing

High-performance computing (HPC) and the cloud have evolved independently, specializing their innovations into performance or productivity. Acceleration as a Service (XaaS) is a recipe to empower both fields with a shared execution platform that provides transparent access to computing resources, regardless of the underlying cloud or HPC service provider. Bridging HPC and cloud advancements, XaaS presents a unified architecture built on performance-portable containers. Here, our converged model concentrates on low-overhead, high-performance communication and computing, targeting resource-intensive workloads from climate simulations to machine learning. XaaS lifts the restricted allocation model of Function as a Service (FaaS), allowing users to benefit from the flexibility and efficient resource utilization of serverless computing while supporting long-running and performance-sensitive workloads from HPC.

97 MATHEMATICS AND COMPUTING↗

Aging Effect Analysis of PV Inverter Semiconductors for Ancillary Services Support

PV inverters can provide reactive power while generating active power. An ongoing microgrid implementation at Duke Energy actively engages non-utility PVs to generate/absorb reactive power in support of ancillary services to increase microgrid resiliency during extreme events. PV systems are requested to provide reactive power support: 1) in response to grid voltage variation to better regulate the local voltage; or 2) in response to utility incentives, such as following Transactive Energy System (TES) incentives. However, providing ancillary services might shorten the lifetime expectation of PV inverter semiconductors. This paper summarizes the potential impacts on a PV inverter semiconductor's lifetime when providing ancillary services. The analysis presented in this research work shows that providing reactive power support will increase the mean junction temperature and the junction temperature variation of the inverter diodes. This increased junction temperature will eventually lead to shorter diode lifetime. The lifetime estimation of semiconductors is briefly reviewed. The power losses of PV inverter semiconductors are derived as a support analysis to the junction temperature calculation. In addition, the impact of the filtering inductor on the semiconductor current distribution is discussed. The theoretical analysis presented in this research work is supported by simulation results.

14 SOLAR ENERGY↗

Scheduler Modeling of IBR Plants for Providing Ancillary Services [SWR-25-16]

Inverter-based resources (IBRs) have been integral components of modern power systems and their capability in providing grid services have been widely studied. To promote the deployment of IBR grid services in real utility operation, this software proposes a scheduler model for IBRs. The energy and reserve are co-optimized in day-ahead, various ancillary services, including operating reserve provision, peak load reduction, voltage regulation and power factor control are integrated in the model.

Wang, Xiaofei [National Renewable Energy Laborator↗

Understanding the Costs and Barriers of Residential Electrical Panel and Service Upgrades

Upgrading electrical panels and services in U.S. homes represents a significant barrier to building modernization, imposing considerable costs, delays, and procedural uncertainties on homeowners, contractors, utilities, and building departments. Although cost databases document individual infrastructure activities, they rarely capture the integrated, whole-project perspective required to understand how electrical upgrades are planned, executed, and regulated. Existing research is often geographically constrained, narrowly scoped, or derived from limited samples, leaving significant knowledge gaps unaddressed. This study examines the timelines and costs associated with residential electrical panel and service upgrades using data from a national cross- sectional survey conducted in summer 2025. The survey captured responses from 140 stakeholders across 34 states, including building industry professionals, utility staff, and building department staff. Findings indicate that project duration and cost increase substantially with building size though patterns vary by infrastructure type. Most single-family and small multifamily projects were completed within 30 days, whereas medium and large multifamily buildings show longer and less predictable timelines. Service rating increases modestly extend project duration, but building type and size were the primary determinants of delays. Cost patterns were similar: customer-side equipment and panel replacements scale predictably with building size, while utility-side costs are highly variable, often triggered by threshold-driven infrastructure upgrades such as transformer replacements. Permit fees vary considerably between jurisdictions but generally represent a minor proportion of total project costs. These findings identify electrical upgrades as a significant barrier to residential building costs and highlight the need for improved stakeholder coordination, streamlined permitting, and strategies that reduce upgrade requirements while maintaining safety and code compliance.

Casquero-Modrego, Nuria↗

Meteorological services annual data report for 2018

This document presents the meteorological data collected at Brookhaven National Laboratory (BNL) by Meteorological Services (Met Services) for the calendar year 2018. The purpose is to publicize the data sets available to emergency personnel, researchers and facility operations. Met services has been collecting data at BNL since 1949. Data from 1994 to the present is available in digital format. Data is presented in monthly plots of one-minute data. This allows the reader the ability to peruse the data for trends or anomalies that may be of interest to them. Full data sets are available to BNL personnel and to a limited degree outside researchers. The full data sets allow plotting the data on expanded time scales to obtain greater details (e.g., daily solar variability, inversions, etc.).

54 ENVIRONMENTAL SCIENCES↗

Meteorological services annual data report for 2019

This document presents the meteorological data collected at Brookhaven National Laboratory (BNL) by Meteorological Services (Met Services) for the calendar year 2019. The purpose is to publicize the data sets available to emergency personnel, researchers and facility operations. Met services has been collecting data at BNL since 1949. Data from 1994 to the present is available in digital format. Data is presented in monthly plots of one-minute data. This allows the reader the ability to peruse the data for trends or anomalies that may be of interest to them. Full data sets are available to BNL personnel and to a limited degree outside researchers. The full data sets allow plotting the data on expanded time scales to obtain greater details (e.g., daily solar variability, inversions, etc.).

54 ENVIRONMENTAL SCIENCES↗

Development of Thermal Tomography Imaging System for In-Service Nondestructive Evaluation of Additively Manufactured Components

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of nuclear reactor parts. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to exposure to high temperature, radiation and corrosive environment in a nuclear reactor. Thermal tomography (TT) provides a capability for non-destructive evaluation of sub-surface defects in arbitrary size structures. We investigate TT of AM stainless steel 316L specimen with imprinted internal porosity defects using relatively low-cost, small form factor infrared (IR) camera based on uncooled micro bolometer detector. Sparse coding related K-means singular value decomposition (SVD) machine learning, image processing algorithms are developed to improve quality of TT images through removal of Additive white Gaussian noise without blurring the images. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact TT can also be used for in-service nondestructive evaluation (NDE). With capability to perform in-service NDE of the AM component lifecycle, TT data can be used for development of a component digital twin. MIT research reactor (MITR) has been identified as a representative environment to perform investigation of feasibility of in-service NDE during shutdown. Preliminary study of radiation level in the MITR viewport, with geometric parameters potentially compatible with compact TT system, has been conducted.

36 MATERIALS SCIENCE↗