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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 685 records · Page 38

Nonreciprocal Thermal Emitters Using Metasurfaces with Multiple Diffraction Channels

The emissivity and absorptivity of nonreciprocal thermal emitters are not constrained by the well-known Kirchhoff law of thermal radiation, which usually serves as the theoretical basis to characterize thermal properties. When thermal emitters are nondiffracting, which is the case in previous studies of nonreciprocal thermal emitters, the angular distribution of emissivity and absorptivity is mirror symmetric with respect to the normal direction, and the nonreciprocal effect is confined to a relatively narrow angular range. In this work, we consider nonreciprocal thermal emitters that can simultaneously couple to multiple diffraction channels. We show that the symmetry relation between absorptivity and emissivity can be broken in such multichannel emitters. The angular range in which the nonreciprocal effect is strong can also be significantly broadened. Such multichannel emitters can operate as one-way energy splitters. Our work significantly broadens the flexibility of thermal-radiation control in nonreciprocal thermal-emitter design.

42 ENGINEERING↗

Evaluating crystallographic likelihood functions using numerical quadratures

Intensity-based likelihood functions in crystallographic applications have the potential to enhance the quality of structures derived from marginal diffraction data. Their usage, however, is complicated by the ability to efficiently compute these target functions. Here, a numerical quadrature is developed that allows the rapid evaluation of intensity-based likelihood functions in crystallographic applications. By using a sequence of change-of-variable transformations, including a nonlinear domain-compression operation, an accurate, robust and efficient quadrature is constructed. The approach is flexible and can incorporate different noise models with relative ease.

59 BASIC BIOLOGICAL SCIENCES↗

Segmented Energy Routing for a Modular AC/DC Hybrid System

This article presents a modular ac/dc system with both distributed and centralized power ports for energy router (ER) applications. In each module of the described system, photovoltaic (PV) power generation units, battery-type energy storage (ES) units, and critical loads are connected to the cascaded H-bridge (CHB)-organized medium-voltage (MV) dc links, with fully distributed low-voltage (LV) dc power ports. Copies of modules share the centralized load bus and interact with an MV ac grid in parallel. Hybrid power port (HPO) assigns flexibility to the system but makes energy routings a necessity for stable operation. In this article, a segmented energy management strategy for the HPO-ER is proposed. In terms of the grid-side power transferring, the system ratings are intentionally designed to match significant power imbalance. Focally, a segmented energy management strategy is proposed to realize fully autonomous energy routing involving MV ac grid, distributed PV generations, distributed battery storages, and LV load. The system is proven to be stable using the derived impedance-based model considering the interaction between power blocks. The feasibility of the topology and control strategy is also verified through software simulation, laboratorial hardware prototype experiment, and hardware-in-the-loop (HIL) emulation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Two-Stage Approach for PV Inverter Engagement in Power Factor Correction and Voltage Regulation

The rapid integration of distributed energy resources, like solar photovoltaics (PVs), can lead to overvolt-age challenges due to reverse power flow and a noticeable decrease in power factor at the substation interface. While existing literature extensively explores utilizing smart inverter capabilities for reactive power flexibility using a volt-var curve (VVC), obtaining time-varying operating points of such curves in real-time is challenging due to computational demands and communication requirements. Similarly, employing optimization-based approaches for reactive power control and active voltage regulation in large-scale distribution feeders is difficult due to the complexity of the problem and the challenges in effectively engaging customer-owned resources. This paper proposes a two-stage strategy to harness smart inverters for reactive power support. The first stage formulates short-term planning by optimally designing VVCs (on a daily or hourly basis) for large-scale solar PVs based on projected system needs and communicating optimal curves to smart inverters in advance. Subsequently, the second stage employs a transactive-based method to involve customer-owned PVs for reactive power support, effectively enhancing overall system performance and addressing real-time demands. In conclusion, the efficacy of this approach will be demonstrated using real-world distribution circuits provided by Vermont Electric Power Company (VELCO) and Vermont Electric Cooperative (VEC).

Poudel, Shiva [Pacific Northwest National Laborato↗

otsdaq

otsdaq is a Ready-to-Use data-acquisition (DAQ) solution aimed at scaling down to test-beam, detector development, and other rapid-deployment scenarios; and scaling up through the development cycle to fullscale production and operation. otsdaq uses the artdaq DAQ framework under-the-hood, providing flexibility and scalability to meet evolving DAQ needs. otsdaq provides a library of supported front-end boards and firmware modules which implement a custom UDP protocol. Additionally, an integrated Run Control GUI and readout software are provided, preconfigured to communicate with otsdaq firmware.

Rivera, Ryan [Fermi National Accelerator Laborator↗

Report for LANSCE Futures Spring 2021 Workshop Series

The Los Alamos Neutron Science Center (LANSCE) has a long and successful history of delivering high-impact science for NNSA missions. The breadth of science LANSCE delivers is enabled by a unique combination of beam power, flexibility, and authorization basis. Though LANSCE is entering its 50th year of operations, current plans for the stockpile require LANSCE capabilities beyond 2050. These requirements demand a technical conversation about the accelerator and the long-term scientific vision for the facility, so we convened a set of workshops to initiate that conversation. The LANSCE Futures workshops spanned three capability areas of LANSCE: dynamic radiography, scattering science, and nuclear science. Participants included the relevant experts from the programs sponsoring LANSCE, the experimentalists utilizing the end-stations, and accelerator systems experts. A final workshop combined the three focus areas to begin the conversation about capabilities that could meet future mission needs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Bamboo Bio-composite Truck/Trailer Decking

Bamboo is one of the fastest growing plants in the world. Massively productive, bamboo will maintain that productivity with limited inputs and minimal management resulting in predictable volume and operating margins and with low overhead. The goal of this project was to develop a bamboo bio-composite trailer decking product that replaces apitong, is lighter weight, stronger and luminescent. The collaboration partners, Fontaine, Resource Fiber and IACMI, worked closely to develop the bamboo bio-composite decking to Fontaine Trailer’s (end-user) specifications. The various technological objectives were (a) To conduct a comprehensive Design of Experiments study for bamboo composites to understand the structure-property relationships for different resin composites and bamboo forms (strips, woven, bulk etc); (b) To establish the nail pull out characteristics of trailer deck geometry bamboo composite form. The nail pull out is a critical test in trailer decks; (c) To design, process and prototype select number of trailer decking planks for Fontaine evaluation; and (d) To conduct life cycle analysis to conduct energy calculations from the various conversion steps of the bamboo from crop to product. The project meets DOE/IACMI metrics of reduced embodied energy, lightweighting and lowering the cost of the end product. It also offers a green solution to a value-added application, i.e. trailer decking. The development goals and benefits of bamboo composite decking included: A. Decreased weight when compared to Apitong and Gen 1, thereby reducing operating costs and petroleum usage due to increased miles per gallon. B. Flexibility to allow camber design into trailers. C. Luminescence to increase safety during low light and dark conditions. D. Composite material to maximize use of bamboo bio-composites as substitute for petroleum-based composites. E. Embedded layer(s) of conditioned bamboo for added strength and stability. F. Improved safety over Apitong by temporary cargo indentation in planks for better stability. G. Cradle-to-cradle design so end-of-life becomes beginning-of-life for other products. Resource Fiber’s bamboo biocomposite trailer decking passed nail pullout tests as compared to apitong (incumbent), was lighter weight than apitong, and used less embodied energy particularly when bamboo is sourced domestically. The planks were optimized in the lab setting to the extent possible and successfully installed on the trailer at Fontaine for field testing. Despite the process not being fully optimized due to through-heat and tooling limitations within the budget constraints, the prototype decking withstood 400 cycles of reverse fatigue loading of a 107,000 lb Caterpillar 349F which was extreme conditions of field testing by Fontaine Trailer. Resource Fiber plans to outsource production of a next round of planks with a commercial pultrusion processor, then to do a re-test with Fontaine Trailers. Tooling specific to the part is required. Long-term commercial plans are to continue outsourcing production while supplying bamboo fiber and mats. Commercial markets include heavy haul trailers, military trailers, and decking for marine, industrial and residential use.

36 MATERIALS SCIENCE↗

Geographically Distributed Co-Simulation for the Interplay of Integrated Energy Systems and Power Grid

The increased penetration of renewable generation induces unbalanced demand-supply on a power grid, while integrated energy systems (IES) can provide high part-load efficiency and high flexibility to support grid resilience. To study the transients and improve dynamic operability, it’s important to investigate the interplay between IES and power grid concurrently using real-time co-simulation approaches. In this presentation, we showed the previous co-simulation test between NETL and INL and discussed how this co-simulation can be beneficial for both IES and power grid research. In addition, we gave an overview about the SuperLab2.0 project, which was a federated national platform to address future power grid challenges. (Virtual presentation to the MILLENNIUM CLEAN and SUSTAINABLE POWER workshop 2025).

Co-simulation↗

Electric Vehicle Charging Management in Smart Energy Communities to Increase Renewable Energy Hosting Capacity

Abnormal climates due to global warming have emerged as a big concern in the global community. To mitigate climate change and achieve sustainability, distributed energy resources (DERs), including solar and wind, have been recently deployed in power systems. As the penetration level of DERs has increased, however, it caused a multitude of issues in the power systems, such as voltage fluctuation in the distribution network limiting renewable hosting capacity. On the other hand, the electric vehicle (EV) industry is rapidly growing to facilitate the transition to a carbon-neutral community, illuminating the potential of EVs as a flexible grid asset to mitigate some of the issues and improve grid operation, if properly exploited. To explore the potential of EVs, this paper proposes an EV scheduling strategy. By using an optimal EV charging scheduling proposed, distribution system operators (DSOs) can minimize their operating costs and stably operate the system with a high level of DERs. To validate the method, a modified IEEE 33-bus system with DERs is developed. The case study shows the proposed scheduling strategizes EV charging to reduce the cost of PV curtailment. In the study, the method outperforms the renewable-only case with curtailment by 4.97% in DSO cost. It also demonstrates its potential to increase the renewable hosting capacity by harmonizing EV charging with renewables.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗

OpenACC unified programming environment for GPU and FPGA multi-hybrid acceleration

Attached accelerators have been frequently used in recent High Per- formance Computing (HPC) systems because of their high performance/power ratio. In particular, the Graphics Processing Unit (GPU) is the most popu- lar accelerator owing to its high peak FLOPS performance and high memory bandwidth supported by HBM2, etc. However, the performance of GPU depends highly on a large degree of SIMD parallelism and has difficulty sustaining a high performance on programs with frequent branch operations or a partially low degree of parallelism.By contrast, a Field Programmable Gate Array (FPGA) has received attention as a different type of accelerator than GPU as a fully reconfigurable processor fitting the target applications. The high performance of FPGA is mainly provided by a pipelined operation and optimized circuit suitable for any operation even with frequent conditional branches. We have been focusing on the flexibility of FPGA to compensate for the weakness of GPU. We believe that the coupling of GPU with FPGA can result in one of the most powerful accelerating platforms available.However, the program coding of GPU and FPGA coupling can be quite difficult for application users. Traditionally, CUDA by NVIDIA has been the most popular programming language with the largest share of GPUs used in HPC, whereas a hardware description language such as Verilog HDL has been used in FPGA programming. OpenCL coding has recently become available even on high-end FPGAs. Moreover, several recent studies have also enabled the OpenACC coding for use in FPGA. In this study, we provide a unified programming system based on OpenACC for a platform equipped with both GPU and FPGA aiming at the next-generation accelerated supercomputer framework. Our programming environment is called Multi-Hybrid OpenACC Translator (MHOAT), and in this paper, we describe the basic concept and prototype system of MHOAT based on an evaluation on the amount of coding required and the performance of a hybrid multi-device accelerated system.

Tsunashima, Ryuta↗

Sparse Matrix-Based HPC Tomography

Tomographic imaging has benefited from advances in X-ray sources, detectors and optics to enable novel observations in science, engineering and medicine. These advances have come with a dramatic increase of input data in the form of faster frame rates, larger fields of view or higher resolution, so high performance solutions are currently widely used for analysis. Tomographic instruments can vary significantly from one to another, including the hardware employed for reconstruction: from single CPU workstations to large scale hybrid CPU/GPU supercomputers. Furthermore, flexibility on the software interfaces and reconstruction engines are also highly valued to allow for easy development and prototyping. This paper presents a novel software framework for tomographic analysis that tackles all aforementioned requirements. The proposed solution capitalizes on the increased performance of sparse matrix-vector multiplication and exploits multi-CPU and GPU reconstruction over MPI. Furthermore, the solution is implemented in Python and relies on CuPy for fast GPU operators and CUDA kernel integration, and on SciPy for CPU sparse matrix computation. As opposed to previous tomography solutions that are tailor-made for specific use cases or hardware, the proposed software is designed to provide flexible, portable and high-performance operators that can be used for continuous integration at different production environments, but also for prototyping new experimental settings or for algorithmic development. The experimental results demonstrate how our implementation can even outperform state-of-the-art software packages used at advanced X-ray sources worldwide.

97 MATHEMATICS AND COMPUTING↗

A Distributionally Robust Optimization Framework for Stochastic Assessment of Power System Flexibility in Economic Dispatch

Given the complexity of power systems, particularly the high-dimensional variability of net loads, accurately depicting the entire operational range of net loads poses a challenge. To address this, recent methodologies have sought to gauge the maximum range of net load uncertainty across all buses. In this paper, we consider the stochastic nature of the net load and introduce a distributionally robust optimization framework that assesses system flexibility stochastically, accommodating a minimal extent of system violations. We verify the proposed method by solving the flexibility of the economic dispatch problem on four distinct IEEE standard test systems. Compared to traditional deterministic flexibility evaluations, our approach consistently yields less conservative flexibility outcomes.

distributionally robust optimization↗

Enhancing Building Energy Efficiency through Advanced Sizing and Dispatch Methods for Energy Storage

Energy storage and electrification of buildings hold great potential for future decarbonization. However, there are several technical and economic barriers that prevent large-scale adoption and integration of energy storage in buildings. These barriers include integration with building control systems, high capital costs, and the necessity to identify and quantify value streams for different stakeholders. To overcome these obstacles, it is crucial to develop advanced sizing and dispatch methods to assist planning and operational decision-making for integrating energy storage in buildings. This work develops simple and flexible optimal sizing and dispatch framework for thermal energy storage (TES) and battery energy storage (BES) systems in large-scale office building. The optimal sizes of TES, BES, as well as other building assets are determined in a joint manner instead of sequentially to avoid sub-optimal solutions. The interaction between the sizing at the planning stage and hourly or sub-hourly dispatch at the operating stage is explicitly modeled. The solution is determined considering both capital costs in optimal sizing and operational benefits in optimal dispatch. Comprehensive assessments are performed using simulation studies to quantify potential energy, economic, and emission benefits by different utility tariffs and climate locations, to improve our understanding of the techno-economic performance of different TES and BES systems, and to identify barriers for adopting energy storage for buildings. Finally, the proposed framework will provide guidance to a broad range of stakeholders to properly design energy storage in buildings and maximizes potential benefits, thereby advancing affordable building energy storage deployment and helping us accelerating the transition towards a cleaner and more equitable energy economy.

Yu, Mingyung↗

Analysis of the Aeroelastic Dynamics of Lightweight Flexible Variations of the SNL-NRT Turbine

Current trends show that wind turbines are growing in size to meet a rising demand for renewable energy generation, and their upscaled rotors have inherently become more flexible to maintain a proportionally lighter design. This is because larger rotors must be less massive relative to their diameter to minimize the levelized cost of energy (LCOE), which means that blades that are notably less stiff are produced as a result. These structural changes to blades are often reflected in their compromised aeroelastic stability and amplified deformation during operation, which has the potential to decrease the blade’s expected lifetime and the performance of the machine overall. Variations in blade flexibility are also known to influence vortex-wake structures downstream of the turbine, causing patterns of velocity deficit to evolve in ways that affect the performance of other turbines in the farm. This research explores how the increased flexibility of modern utility-scale wind turbine blades influences rotor aeroelastic behavior and interactions with farm flow. High-fidelity simulations of Sandia National Laboratories’ (SNL) National Rotor Testbed (NRT) wind turbine are presented. Flexible variations of the NRT baseline blade are simulated in a variety of realistic operational conditions typically expected at the SNL’s SWiFT facility in Lubbock, Texas. Solutions are then compared to investigate how specific changes to the structural properties of the NRT baseline blade’s design and construction can influence its aeroelastic response at the rotor and the evolution of the turbine’s wake.

Farrell, Alayna (ORCID:000000023555720X)↗

Optimizing HVAC Operations in Multi-unit Buildings for Grid Demand Response

The thermal inertia of buildings, along with the flexibility associated with thermostatically controlled loads (TCL) allows heating ventilation and cooling (HVAC) systems to be used for grid demand response (DR). In this work, we consider an HVAC system that serves multiple units in a residential building to meet their space heating requirements. We aim to determine the optimal power flow to each unit that minimizes the power costs incurred by the building's occupants while keeping in consideration their thermal comfort. The DR program is assumed to allow the building temperatures to deviate from the set-points up to a maximum limit. Despite the complex, non-linear structure of the problem, we show how the optimal solutions can be obtained efficiently using quadratic programming. Since HVAC systems can run on either electricity or natural gas, we study the efficacy of the DR regime for both hourly electricity prices and flat gas prices over the course of 24 hours. Finally, we run simulations to determine the optimal thermal power and the evolution of unit temperatures for various energy pricing schemes.

Naqvi, Syed A.↗

NSUF University Research Reactor Fitness Workshop

University research reactors have been a cornerstone of nuclear engineering research and education since the first reactor was deployed at North Carolina State University in the 1950s. The population of university reactors grew to a high of almost 80 in 1970 but has dropped to 25 operating today, also shrinking the community, availability of vendors and the talent pipeline. The nation’s fleet of TRTRs serves as a vital resource for educating the next generation of nuclear engineers and as a flexible testbed for innovative reactor technologies. Typically, the reactors have a very small staff with responsibilities ranging through research and operations, isotope production, regulatory compliance, facility maintenance, and university teaching obligations. Knowledge transfer and staffing were identified as critical areas in a recent study of US university research reactor fitness. This panel discusses the unique challenges and potential solutions to these issues.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Operational Simulation of Multi-Functional Charging Station for Sustainable Transportation

As transportation systems move toward electrification and decarbonization, multifunctional charging stations (MFCS) are emerging as key infrastructure for electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs). This paper presents a simulation model of an MFCS that integrates solar photovoltaic (PV), wind power, battery storage, hydrogen (\mathrm{H}_{2}) production, dual-pressure \mathrm{H}_{2} storage, fuel cells, and dynamic grid interactions. The model simulates daily operations using 5 -minute resolution data to capture realtime variability in renewable energy (RE), demand, and electricity prices. A flexible dispatch algorithm dynamically allocates energy for EV charging, \mathrm{H}_{2} production, storage, and grid transactions while respecting system constraints. Results show that the MFCS effectively prioritizes RE usage, minimizes waste, meets diverse energy demands, and achieves net operational profit. The model serves as a valuable decision-support tool for designing and optimizing integrated clean energy hubs for zero-emission transportation.

Gbadegoye, Jeremiah [University of Tennessee, Knox↗