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At least 775 records · Page 43

Hydrogen Fuel Cell Electric Bus (FCEB) Evaluations in US Public Transit Service

The National Renewable Energy Laboratory (NREL) is a Department of Energy (DOE) national laboratory focused on renewable energy and energy efficiency. NREL has evaluated alternative fuel and advanced propulsion transit buses for DOE and the U.S. Department of Transportation's Federal Transit Administration (FTA). These evaluations are focused on determining the status of fuel cell systems and the corresponding infrastructure in transit applications to help DOE and FTA assess the progress toward technology readiness. For the last 19 years NREL has evaluated FCEBs in service around the United States and in Canada. The results of these evaluations have been published in numerous reports that compare FCEB performance to conventional technology as well as document the implementation experience and lessons learned by the transit agencies and their demonstration teams. Currently, 70 fuel cell buses are in active service in the US and 66 FCEBs are in development. NREL is evaluating a subset of the active FCEBs that includes three transit agencies demonstrating 25 fuel cell electric buses in California. One bus has exceeded 35,000 hours in service and 12 have exceeded 25,000 hours. Fuel economy for the current generation of FCEBs has improved 35% over the previous generation and is double that of conventional buses. Maintenance cost for FCEBs is equivalent to diesel and BEBs. The most up-to-date performance results will be presented, including fuel economy, availability, reliability, and operational costs.

bus↗

Evaluating a Laboratory Flume Microbiome as a Window Into Natural Riverbed Biogeochemistry

Riverbeds are hotspots for microbially-mediated reactions that exhibit pronounced variability in space and time. It is challenging to resolve biogeochemical mechanisms in natural riverbeds, as uncontrolled settings complicate data collection and interpretation. To overcome these challenges, laboratory flumes are often used as proxies for natural riverbed systems. Flumes capture spatiotemporal variability and thus allow for controlled investigations of riverbed biogeochemistry. These investigations implicitly rely on the assumption that the flume microbiome is similar to the microbiome of natural riverbeds. However, this assumption has not been tested and it is unknown how the microbiome of a flume compares to natural aquatic settings, including riverbeds. To evaluate the fundamental assumption that a flume hosts a microbiome similar to natural riverbed systems, we used 16s rRNA gene sequencing and publicly available data to compare the sediment microbiome of a single large laboratory flume to a wide variety of natural ecosystems including lake and marine sediments, river, lake, hyporheic, soil, and marine water, and bank and wetland soils. Richness and Shannon diversity metrics, analyses of variance, Bray-Curtis dissimilarity, and analysis of the common microbiomes between flume and river sediment all indicated that the flume microbiome more closely resembled natural riverbed sediments than other ecosystems, supporting the use of flume experiments for investigating natural microbially-mediated biogeochemical processes in riverbeds.

54 ENVIRONMENTAL SCIENCES↗

Effects of Au2+ irradiation induced damage in a high-entropy pyrochlore oxide single crystal

Here, we report an ion-irradiation study of a compositionally complex (high-entropy) pyrochlore oxide. The damage produced from 4 MeV Au 2+ ion irradiation on single crystal (Yb 0.2 Tm 0.2 Lu 0.2 Ho 0.2 Er 0.2 ) 2 Ti 2 O 7 aligned along the [100] direction is investigated at room temperature by Rutherford backscattering spectrometry in channeling mode (RBS/C). Damage profiles based on RBS/C are presented and compared to single-component pyrochlore titanate oxides to evaluate the relative resistance to irradiation-induced amorphization. The results show that this high-entropy pyrochlore goes amorphous at a dose of 0.13 dpa, which is comparable to that of single-component pyrochlores previously studied. Transmission electron microscopy images unveil the damaged surface layer, which is consistent with the RBS/C results.

36 MATERIALS SCIENCE↗

Characterizing uncertainties in ground “truth” of precipitation over complex terrain through high-resolution numerical modeling

Ground observation of precipitation over complex terrain is subject to large uncertainties due to inadequate sampling. This study explores a method that combines limited gauge data and a high-resolution numerical simulation to quantify the precipitation uncertainties in central Himalaya. Specifically, the Coefficient of spatial Variability (CV) of precipitation and the minimum Number of Required Stations (NRS) to obtain areal-mean precipitation ground truth values within a 0.25-degree area are investigated using fine-scale meteorological simulation at 1.5 km grid spacing. Evaluation over a densely-gauged area demonstrates comparable CV and NRS values between station observations and simulations. The simulated CV and NRS values in a larger area show a strong and positive dependence on each other and an expected positive (negative) correlation with topographic complexity (temporal scale). The proposed method sheds lights on evaluating precipitation products and holds promise for informing the layout of rain gauge networks in complex terrain.

Ouyang, Lin↗

Rucio beyond ATLAS: experiences from Belle II, CMS, DUNE, EISCAT3D, LIGO/VIRGO, SKA, XENON

For many scientific projects, data management is an increasingly complicated challenge. The number of data-intensive instruments generating unprecedented volumes of data is growing and their accompanying workflows are becoming more complex. Their storage and computing resources are heterogeneous and are distributed at numerous geographical locations belonging to different administrative domains and organisations. These locations do not necessarily coincide with the places where data is produced nor where data is stored, analysed by researchers, or archived for safe long-term storage. To fulfil these needs, the data management system Rucio has been developed to allow the high-energy physics experiment ATLAS at LHC to manage its large volumes of data in an efficient and scalable way. But ATLAS is not alone, and several diverse scientific projects have started evaluating, adopting, and adapting the Rucio system for their own needs. As the Rucio community has grown, many improvements have been introduced, customisations have been added, and many bugs have been fixed. Additionally, new dataflows have been investigated and operational experiences have been documented. In this article we collect and compare the common successes, pitfalls, and oddities that arose in the evaluation efforts of multiple diverse experiments, and compare them with the ATLAS experience. This includes the high-energy physics experiments Belle II and CMS, the neutrino experiment DUNE, the scattering radar experiment EISCAT3D, the gravitational wave observatories LIGO and VIRGO, the SKA radio telescope, and the dark matter search experiment XENON.

Lassnig, Mario↗

Forward modeling approach to nuclear reaction cross sections: Applications in neutron inelastic scattering

The development of nuclear reaction models for the production of evaluated nuclear data has traditionally been performed by comparing measured cross sections with predictions from reaction model codes whose physical input parameters are adjusted to obtain the best agreement between measured and modeled results. To more directly probe reaction model inputs, this work introduces a forward modeling approach to experimental reaction cross-section determination, where the most important physical input parameters to reaction model calculations are obtained via 𝜒 2 minimization between measured and calculated observables. This was demonstrated using data collected by the Gamma Energy Neutron Energy Spectrometer for Inelastic Scattering (GENESIS) at the 88-inch cyclotron at Lawrence Berkeley National Laboratory, a detection array consisting of organic liquid scintillators and high-purity germanium (HPGe) detectors. Using a broad-spectrum neutron beam and a 99.98%-enriched 56 Fe target, GENESIS was used to perform a simultaneous measurement of 56 Fe 𝛾-ray production cross sections and secondary neutron energy and angle distributions. The results of the forward modeling approach to the determination of energy-differential 𝛾-ray production cross sections for the yrast 4 + → 2 + and 6 + → 4 + transitions, as well as eight other off-yrast transitions, were compared against those obtained using conventional techniques, and the results are in good agreement. In addition to discrete 𝛾-ray yield total scattered neutron energy-angular distributions as a function of incident neutron energy were also obtained using forward modeling and found to agree with evaluated data, with the exception of elastic scattering at small angles. The fitted reaction model parameters obtained through forward modeling were also used to calculate the cross section for the unobserved (𝑛, 2⁢𝑛) reaction; excellent agreement with the current evaluation was obtained, providing a validation of the predictive capabilities of the forward model approach. This work bridges the gap between nuclear data experiment and evaluation by providing a new means for extracting inelastic neutron-scattering cross sections and neutron-induced 𝛾-ray production data while directly probing reaction model physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Substitution of virgin carbon fiber with low-cost recycled fiber in automotive grade injection molding polyamide 66 for equivalent composite mechanical performance with improved sustainability

Recycled carbon fiber has historically proven challenging to integrate into composite manufacturing due in no small part to the low-density, randomly oriented, discontinuous fiber format that results from typical recycling. Discontinuous fiber requires the use of alternative technologies than those traditionally applied to continuous fiber (e.g., hand lay-up, winding). Extrusion compounding is one such applicable technology, but material transfer into the system requires alternative feeding equipment or the use of an altered procedure as trialed in this research. In this study, an injection molding compound for automotive applications was prepared with recycled carbon fiber and compared against an existing commercial compound. Input fibers and molded compound were evaluated for mechanical performance, while relevant variables such as compounded fiber alignment and aspect ratio were compared to the existing baseline material to confirm a like-for-like composite material structure. Overall, analysis indicates that recycled fiber performs similarly to virgin fiber reinforcement, demonstrating that recycled fiber may be a viable drop-in replacement for short-fiber discontinuous applications.

42 ENGINEERING↗

Photonuclear Reaction Types Map to ENDF Reaction Type Numbers MT

In the ENDF format, photonuclear cross secCons are stored in File = 3 under the NSUB = 0 sub-library. The type of reacCon data and the products resulCng from that reacCon are idenCfied by an integer number from 1 to 999, called MT number. However, the ENDF manual is wriPen with a strong focus on neutron induced reacCons and the meaning of MT numbers in the context of photonuclear reacCons can be at Cmes confusing and the assessment of evaluated photonuclear data may require summing various MT numbers to obtain the desired cross secCons to compare with experimental data. An important step in assessing the quality of evaluated data for photonuclear cross secCons is therefore to clarify the mapping between MT numbers and the nomenclature used to describe photonuclear reacCons in the literature. The intent of this document is to provide such a map.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Semi-automatic image annotation using 3D LiDAR projections and depth camera data

Efficient image annotation is necessary to utilize deep learning object recognition neural networks in nuclear safeguards, such as for the detection and localization of target objects like nuclear material containers (NMCs). This capability can help automate the inventory accounting of different types of NMCs within nuclear storage facilities. The conventional manual annotation process is labor-intensive and time-consuming, hindering the rapid deployment of deep learning models for NMC identifications. This paper introduces a novel semi-automatic method for annotating 2D images of nuclear material containers (NMCs) by combining 3D light detection and ranging (LiDAR) data with color and depth camera images collected from a handheld scan system. The annotation pipeline involves an operator manually marking new target objects on a LiDAR-generated map, and projecting these 3D locations to images, thereby automatically creating annotations from the projections. The semi-automatic approach significantly reduces manual efforts and the expertise in image annotation that is required to perform the task, allowing deep learning models to be trained on-site within a few hours. The paper compares the performance of models trained on datasets annotated through various methods, including semi-automatic, manual, and commercial annotation services. The evaluation demonstrates that the semi-automatic annotation method achieves comparable or superior results, with a mean average precision (mAP) above 0.9, showcasing its efficiency in training object recognition models. Additionally, the paper explores the application of the proposed method to instance segmentation, achieving promising results in detecting multiple types of NMCs in various formations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

High-entropy Li-rich layered oxide cathode for Li-ion batteries

High-entropy oxides (HEOs) are emerging as promising cathode materials for Li-ion batteries (LIBs) due to their stable solid-state phase and compositional flexibility. Herein, we investigate the structural and electrochemical properties of a novel non-equimolar high-entropy cathode material, termed high-entropy Li-rich layered oxide (HE-LLO, Li 1.15 Na 0.05 Ni 0.19 Mn 0.56 Fe 0.02 Mg 0.02 Al 0.02 O 1.97 F 0.03 ), in comparison to a pristine Li-rich layered oxide (PR-LLO, Li1.2Ni0.2Mn0.6O2). The incorporation of multiple cations (Na + , Al 3+ , Mg 2+ , Fe 3+ ) and anion (F - ) into HE-LLO introduces compositional diversity, enhancing structural stability through the entropy stabilization effect. Theoretical calculations confirm a significantly higher configurational entropy in HE-LLO compared to PRLLO, supporting its high-entropy nature. Electrochemical evaluations demonstrate that HE-LLO exhibits considerable capacity retention, preserving 76.8 % of its discharge capacity at 0.5C after 200 cycles, compared to only 36.2 % for PR-LLO. Even under high-temperature conditions, HE-LLO outperformed PR-LLO, maintaining 76.1 % of its discharge capacity after 100 cycles at 5C, while PR-LLO retained only 12.4 %. These enhancements are attributed to the improved phase reversibility and higher Li + ion diffusion coefficients of HE-LLO, validated by ex-situ characterizations using a synchrotron X-ray technique, along with density functional theory (DFT) calculations. In conclusion, these findings highlight the promise of non-equimolar HEOs as a novel design strategy for highperformance cathode materials.

25 ENERGY STORAGE↗

An Evaluation of Energy Storage Cost and Performance Characteristics

The energy storage industry continues to expand globally as costs continue to fall and opportunities in consumer, transportation and grid applications are defined. As the rapid evolution of the industry continues, it has become increasingly important to understand how varying technologies compare in terms of cost and performance. This paper defines and evaluates cost and performance parameters of six battery energy storage technologies (BESS) - lithium-ion batteries, lead-acid batteries, redox flow batteries, sodium-sulfur batteries, sodium metal halide batteries, and zinc-hybrid cathode batteries - four non-BESS storage technologies - pumped storage hydropower, flywheels, compressed air energy storage, and ultracapacitors - and combustion turbines. Cost and performance information was compiled based on an extensive literature review, conversations with vendors and stakeholders, and costs of systems procured at sites across the United States. Detailed cost and performance estimates are presented for 2018 and projected out to 2025. Annualized costs were also calculated for each technology.

Mongird, Kendall↗

Exploring the benefits of using co-packaged optics in data center and AI supercomputer networks: a simulation-based analysis [Invited]

We investigate the advantages of using co-packaged optics in next-generation data center and AI supercomputer networks. The increased escape bandwidth offered by co-packaged optics provides multiple possibilities for building 50T switches and beyond, expanding the opportunities in both the data center and supercomputing domains. Furthermore, this provides network architects with the opportunity to expand their design space and develop simplified networks with enhanced network locality properties. Co-packaging at the switch and server points enables networks with double capacity while reducing the switch count by 64% compared to state-of-the-art systems. We evaluate these concepts through discrete-event simulations using all-to-all and all-reduce traffic patterns that simulate collective communications commonly found in network-bound applications. Initially, we investigate the all-to-all overhead involved in distributing the virtual machines of the applications across multiple leaf switches and compare it to the scenario in which all VMs are placed under a single switch. Subsequently, we evaluate the performance of an AI supercomputing cluster by simulating both patterns for different message sizes, while also varying the number of participating nodes. The results suggest that networks with improved locality properties become increasingly important as the network stack operates at higher speeds; for a stack latency of 1.25 µs, placing the applications under multiple switches can result in up to 68% higher completion times than placing them under a single switch. For AI supercomputers, significant improvements are observed in the mean server throughput, reaching more than 90% for configurations involving 256 nodes and message sizes of at least 128 KiB.

99 GENERAL AND MISCELLANEOUS↗

Additive Polynomial Time Integrators, Part I: Framework and Fully Implicit-Explicit Collocation Methods

In this paper we generalize the polynomial time integration framework to additively partitioned initial value problems. The framework we present is general and enables the construction of many new families of additive integrators with arbitrary order-of-accuracy and varying degree of implicitness. In this first work, we focus on a new class of implicit-explicit polynomial block methods that are based on fully implicit Runge–Kutta methods with Radau nodes and that possess high stage order. Here, we show that the new fully implicit-explicit (FIMEX) integrators have improved stability compared to existing IMEX Runge–Kutta methods, while also being more computationally efficient due to recent developments in preconditioning techniques for solving the associated systems of nonlinear equations. For PDEs on periodic domains where the implicit component is trivial to invert, we will show how parallelization of the right-hand side evaluations can be exploited to obtain significant speedup compared to existing serial IMEX Runge–Kutta methods. For parallel (in space) finite element discretizations, the new methods can achieve orders of magnitude better accuracy than existing IMEX Runge–Kutta methods and/or achieve a given accuracy several times times faster in terms of computational runtime.

97 MATHEMATICS AND COMPUTING↗

Indirect Tool Condition Monitoring Using Ensemble Machine Learning Techniques

Abstract Tool condition monitoring (TCM) has become a research area of interest due to its potential to significantly reduce manufacturing costs while increasing process visibility and efficiency. Machine learning (ML) is one analysis technique which has demonstrated advantages for TCM applications. However, the commonly studied individual ML models lack generalizability to new machining and environmental conditions, as well as robustness to the unbalanced datasets which are common in TCM. Ensemble ML models have demonstrated superior performance in other fields, but have only begun to be evaluated for TCM. As a result, it is not well understood how their TCM performance compares to that of individual models, or how homogeneous and heterogeneous ensemble models’ performances compare to one another. To fill in these research gaps, milling experiments were conducted using various cutting conditions, and the model groups were compared across several performance metrics. Statistical t-tests were also used to evaluate the significance of model performance differences. Through the analysis of four individual ML models and five ensemble models, all based on the processes’ sound, spindle power, and axial load signals, it was found that on average, the ensemble models performed better than the individual models, and that the homogeneous ensembles outperformed the heterogeneous ensembles.

Engineering↗

On the Feasibility of Simulation-Driven Portfolio Scheduling for Cyberinfrastructure Runtime Systems

Runtime systems that automate the execution of applications on distributed cyberinfrastructures need to make scheduling decisions. Researchers have proposed many scheduling algorithms, but most of them are designed based on analytical models and assumptions that may not hold in practice. The literature is thus rife with algorithms that have been evaluated only within the scope of their underlying assumptions but whose practical effectiveness is unclear. It is thus difficult for developers to decide which algorithm to implement in their runtime systems.To obviate the above difficulty, we propose an approach by which the runtime system executes, throughout application execution, simulations of this very execution. Each simulation is for a different algorithm in a scheduling algorithm portfolio, and the best algorithm is selected based on simulation results. The main objective of this work is to evaluate the feasibility and potential merit of this portfolio scheduling approach, even in the presence of simulation inaccuracy, when compared to the traditional one-algorithm approach. We perform this evaluation via a case study in the context of scientific workflows. Our main finding is that portfolio scheduling can outperform the best one-algorithm approach even in the presence of relatively large simulation inaccuracies.

Casanova, Henri↗

Comparative life cycle assessment of various hydrogen pathways for cleaner methanol synthesis

This study evaluates the potential environmental impacts of e-methanol production using hydrogen from green, yellow, and blue sources, including Gas Switching Reforming for high purity hydrogen production with carbon capture (GSR-H 2 ), and compares their performance across current and renewable energy scenarios. Using a cradle-to-gate life cycle assessment (LCA), the study quantifies impacts across seven TRACI categories. Global warming potential (GWP) ranged from 0.28 kg CO 2 eq/kg MeOH for green hydrogen with renewables to 2.55 kg CO 2 eq/kg MeOH for SMR-CC under grid power. Among the scenarios, renewable electrolysis achieves the lowest GWP, while GSR-H 2 under renewable power offered the best balance of emissions reductions and resource efficiency among the fossil-based routes, offering a viable transitional solution in regions dependent on natural gas infrastructure. The study reveals GSR-H 2 's potential as an alternative to conventional steam methane reforming with carbon capture (SMR-CC), showing its advantages in carbon capture efficiency and reduced life cycle emissions as well as significantly lower water consumption. GSR-H 2 , when powered by renewables, consumed only 1.41 L of water per kg MeOH, an 82% reduction compared to grid-powered electrolysis, highlighting its potential in water-scarce regions. This study is the first to evaluate GSR-H 2 as a hydrogen source for e-methanol, providing new evidence for its role as a cleaner, scalable transitional solution aligned with cleaner production principles.

08 HYDROGEN↗

State Policies on Access to Vaccination Services for Low-Income Adults

Importance State vaccination benefits coverage and access for adult Medicaid beneficiaries vary substantially. Multiple studies have documented lower vaccination uptake in publicly insured adults compared with privately insured adults. Objective To evaluate adult Medicaid beneficiaries’ access to adult immunization services through review of vaccination benefits coverage in Medicaid programs across the 50 states and the District of Columbia. Design, Setting, and Participants A public domain document review with supplemental semistructured telephone survey was conducted between June 1, 2018, and June 14, 2019, to evaluate vaccination services benefits in fee-for-service and managed care organization arrangements for adult Medicaid beneficiaries in the 50 states and the District of Columbia (total, 51 Medicaid programs). Exposures Document review of benefits coverage for adult immunization services and supplemental survey with validation of document review findings. Main Outcomes and Measures Benefits coverage for adult Medicaid beneficiaries and reimbursement amounts for vaccine purchase and administration. Results Public domain document review was completed for all 51 jurisdictions. Among these, 44 Medicaid programs (86%) validated document review findings and completed the survey. Only 22 Medicaid programs (43%) covered all 13 Advisory Committee on Immunization Practices–recommended adult immunizations under both fee-for-service and managed care organization arrangements. Most fee-for-service arrangements (37 of 49) reimbursed health care professionals using any of the 4 approved vaccine administration codes; however, 8 of 49 programs did not separately reimburse for vaccine administration to adult Medicaid beneficiaries. Depending on administration route, median reimbursement for adult vaccine administration ranged from $\$9.81$ to $\$13.98$ per dose. Median per-dose reimbursement for adult vaccine purchase was highest for 9-valent human papillomavirus vaccine ($\$204.87$) and lowest for Haemophilus influenzae type b vaccine ($\$18.09$). Median reimbursement was below the private sector price for 7 of the 13 included vaccines. Conclusions and Relevance Even in programs with complete vaccination benefits coverage, reimbursement amounts to health care professionals for vaccine purchase and administration may not fully cover vaccination provision costs. Reimbursement amounts below costs may reduce incentives for health care professionals to vaccinate low-income adults and thereby limit Medicaid adult beneficiary access to vaccination.

60 APPLIED LIFE SCIENCES↗

Interfacing HDF5 with a scalable object‐centric storage system on hierarchical storage

Summary Object storage technologies that take advantage of multitier storage on HPC systems are emerging. However, to use these technologies at present, applications have to be modified significantly from current I/O libraries. HDF5, a widely used I/O middleware on HPC systems, provides a virtual object layer (VOL) that allows applications to connect to different storage mechanisms transparently without requiring significant code modifications. We recently designed the proactive data containers (PDC) object‐centric storage system that provides the capabilities of transparent, asynchronous, and autonomous data movement taking advantage of multiple storage tiers—a decision that has so far been left upon the user on most current systems. To enable PDC's features through HDF5 without modifying application codes, we have developed an HDF5 VOL connector that interfaces with PDC. We present in this article the connector interface and evaluate its performance on Cori, a Cray XC40 supercomputer located at the National Energy Research Scientific Computing Center (NERSC). Our evaluation demonstrates up to an 8× improvement compared with HDF5 that has the most recent optimizations.

Mu, Jingqing↗