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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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These points are covered in this presentation: Distributed GPU stencil, non-contiguous data; Equivalence of strided datatypes and minimal representation; GPU communication methods; Deploying on managed systems; Large messages and MPI datatypes; Translation and canonicalization; Automatic model-driven transfer method selection; and Interposed library implementation.
Gas sparging is the most commonly used method for delivering CO2 to algal cultures in Open Raceway Ponds (ORPs). While this method is well-tested and effective, these systems experience large amounts of outgassing to the surrounding atmosphere and often achieve carbon utilization efficiencies (CUE) lower than 30%. With such large losses, system are overdesigned to provide CO2 gas in extreme excess, resulting in increased capital and operational expenses. This research is focused on the development, testing, and implementation of a hydrogel membrane seeded with the enzyme carbonic anhydrase and designed to convert gaseous CO2 into aqueous bicarbonate and deliver this inorganic carbon (iC) directly to the algae pond. Despite increased capital expenses for the module, bicarbonate storage tank, and added pumps and infrastructure, preliminary results suggest that the membrane module has the potential to reduce the minimum biomass selling price by 35% by significantly reducing the operational expenditure for CO2.
The U.S. Department of Energy’s Advanced Manufacturing Office (predecessor to AMMTO) established PowerAmerica in December 2014 to develop and accelerate the adoption of wide bandgap (WBG) semiconductor chips and power electronics in manufacturing. The objective was to spark early commercialization of energy efficient products; educate and train the workforce; create high-tech jobs; and nurture the growth of the U.S. WBG semiconductor manufacturing industry. PowerAmerica isled by North Carolina State University by way of a five-year, $140M cooperative agreement with DoE. This private-public partnership with DoE includes member companies ranging from startups and small-medium enterprises to large system integrators, world-class universities, and national labs. The WBG power electronic ecosystem formed by our diverse membership is focused on using advanced manufacturing to 1) lower the cost of silicon carbide and gallium nitride semiconductor devices to be comparable to silicon devices; 2) demonstrate the system benefits and energy efficiency advantages of WBG semiconductor power electronics through system demonstrations that validate their effectiveness; and 3) build an education pipeline for a skilled workforce to meet the future demand for emerging WBG semiconductor markets — and enhance U.S. economic competitiveness globally. PowerAmerica was initially funded in six budget periods, each lasting 12 to 18 months. By the end of Budget Period 6 (August 2023), PowerAmerica had achieved its major objectives in technology development, semiconductor device cost reduction, ecosystem growth and engagement, and education and workforce development. Through strategic foundry investments, we helped to establish the first U.S. SiC foundry (X-FAB) and supported a lab (Microchip) to start SiC volume production. We’ve helped bring together companies from different parts of the supply chain, resulting in several successful new partnerships and business relationships. Through projects with some of the largest manufacturers of energy-intensive equipment in the U.S. — John Deere, GE, United Technologies, Raytheon, Carrier, Toshiba, and others — we have successfully demonstrated the energy and system benefits of WBG technology. We have also harnessed the unique capabilities and facilities of national labs — the Naval Research Laboratory, National Renewable Energy Laboratory, and Argonne National Laboratory — to help solve challenging technical problems for industry. Thanks to our many webinars, tutorials, annual events, and presence at major energy and electronics conferences around the world, the PowerAmerica name has become synonymous with WBG technology advancement. The commercial interest in WBG technology is higher than ever; companies and governments around the world have announced hundreds of millions of dollarsin future investment to build capacity — and compete with silicon in many markets and applications. We have trained hundreds of engineering students, from universities across the U.S., through hands-on projects and WBG coursework. Working professionals have also benefited through the years from our many targeted short courses, tutorials, and technical webinars. In short, PowerAmerica has made great strides in each of our key objectives, and the organization has been operating without government or NC State
Event generators simulate particle interactions using Monte Carlo techniques, providing the primary connection between experiment and theory in experimental high energy physics. These software packages, which are the first step in the simulation worflow of collider experiments, represent approximately 5 to 20% of the annual WLCG usage for the ATLAS and CMS experiments. With computing architectures becoming more heterogeneous, it is important to ensure that these key software frameworks can be run on future systems, large and small. In this contribution, recent progress on porting and speeding up the Madgraph5_aMC@NLO event generator on hybrid architectures, i.e. CPU with GPU accelerators, is discussed. The main focus of this work has been in the calculation of scattering amplitudes and "matrix elements", which is the computational bottleneck of an event generation application. For physics processes limited to QCD leading order, the code generation toolkit has been expanded to produce matrix element calculations using C++ vector instructions on CPUs and using CUDA for NVidia GPUs, as well as using Alpaka, Kokkos and SYCL for multiple CPU and GPU architectures. Performance is reported in terms of matrix element calculations per time on NVidia, Intel, and AMD devices. The status and outlook for the integration of this work into a production release usable by the LHC experiments, with the same functionalities and very similar user interfaces as the current Fortran version, is also described.
With increasing subsystem size and energy, bipartite entanglement entropies of energy eigenstates cross over from the groundstate scaling to a volume law. In previous work, we pointed out that, when strong or weak eigenstate thermalization (ETH) applies, the entanglement entropies of all or, respectively, almost all eigenstates follow a single crossover function. The crossover functions are determined by the subsystem entropy of thermal states and assume universal scaling forms in quantum-critical regimes. This was demonstrated by field-theoretical arguments and the analysis of large systems of non-interacting fermions and bosons. Here, we substantiate such scaling properties for integrable and non-integrable interacting spin-1/2 chains at criticality using exact diagonalization. In particular, we analyze XXZ and transverse-field Ising models with and without next-nearest-neighbor interactions. Indeed, the crossover of thermal subsystem entropies can be described by a universal scaling function following from conformal field theory. Furthermore, we analyze the validity of ETH for entanglement in these models. Even for the relatively small system sizes that can be simulated, the distributions of eigenstate entanglement entropies are sharply peaked around the subsystem entropies of the corresponding thermal ensembles.
Passive surface acoustic wave (SAW) devices are attractive candidates for continuous wireless monitoring of corrosion in large infrastructures. However, acoustic loss in the aqueous medium and limited read range usually create challenges in their widespread use for monitoring large systems such as oil and gas (O&G) pipelines, aircraft, and processing plants. This paper presents the investigation of impedance-loaded reflective delay line (IL-RDL) SAW devices for monitoring metal corrosion under O&G pipeline-relevant conditions. Specifically, we studied the effect of change in resistivity of a reflector on the backscattered signal of an RDL and investigated an optimal range through simulation. This was followed by the experimental demonstrations of real-time monitoring of Fe film corrosion in pressurized (550 psi) humid CO 2 conditions. Additionally, remote monitoring of Fe film corrosion in an acidic solution inside a 70 m carbon steel pipe was demonstrated using guided waves. This paper also suggests potential ways to improve the sensing response of IL-RDLs.
In recent years the understanding on the limits of the smallest possible droplet of the Quark Gluon Plasma has been called into question. Experimental results from both the Large Hadron Collider and the Relativistic Heavy Ion Collider have provided hints that the Quark Gluon Plasma may be produced in systems as small as that formed in p Pb or d Au collisions. Yet alternative explanations still exist from correlations arising from quarks and gluons in a color glass condensate picture. In order to resolve these two scenarios, a system size scan has been proposed at the Large Hadron Collider for collisions of ArAr and OO. Here we make predictions for a possible future run of ArAr and OO collisions at the Large Hadron Collider and study the system size dependence of a variety of flow observables. We find that linear response (from the initial conditions to the final flow harmonics) becomes more dominant in smaller systems whereas linear + cubic response can accurately predict multi-particle cumulants for a wide range of centralities in large systems.
Abstract Today's intermediate‐scale quantum computers, although imperfect, already perform computational tasks that are manifestly beyond the capabilities of modern classical supercomputers. However, so far, quantum‐enabled large‐scale solutions have been realized only for limited set of problems. Here a hybrid algorithm based on phase estimation and classical optimization of the circuit width and depth is employed for solving a specific class of large linear systems of equations ubiquitous to many areas of science and engineering. A classification of linear systems based on the entanglement properties of the associated phase‐estimation unitary operation is introduced, enabling a highly efficient search for solutions that is facilitated by a straightforward matrix‐to‐circuit map. A 2 17 ‐dimensional problem is implemented on several IBM quantum computer superconducting quantum processors, a record‐breaking result for a linear system solved by a quantum computer. Demonstrated realisation sets a clear benchmark in the quest for the future quantum speedup in the linear systems of equations solution.
This paper explores the potential opportunities for implementing file prefetching techniques on large-scale high-performance computing (HPC) systems. Specifically, we investigate the file access patterns of various applications across multiple scientific domains using two years' worth of Darshan I/O traces obtained from the Summit supercomputer. We identify recurring trends and patterns which indicate that prefetching can be effectively leveraged to improve data access performance on HPC systems. This study serves as a valuable reference for system architects and developers in the HPC community, providing insights into the opportunities and challenges associated with enabling file prefetching on large-scale HPC systems.
This paper proposes a model-free decentralized control framework for the voltage regulation of large-scale distribution systems through the coordinated control of PV inverters. This is achieved by developing a novel interaction mechanism between the surrogate model and the centralized training and decentralized execution multiagent deep reinforcement learning framework. Specifically, the sparse Gaussian processes regression method is first utilized to develop the surrogate model of the original distribution system for reward calculation during the training stage, where each agent represents a sub-region in the centralized fashion for coordination strategy learning. After that, the learned control rules are used to inform controllers within each sub-region for real-time decisions with only local measurements. Comparative tests among various methods on the EPRI Ckt5 test system demonstrate the effectiveness of the proposed method.
Large-signal impedance of grid-connected converters can be used to predict resonance-generated distortions in converter-grid systems. Note that the large-signal impedance of a network represents its impedance response for different magnitudes of perturbation injected at its terminals. This paper presents large-signal impedance-based modeling and mitigation of resonance of grid-connected voltage source converters (VSCs). Challenges of large-signal modeling because of the inapplicability of the small-signal approximation are addressed by leveraging the dominating influence of hard nonlinearities (such as pulse-width modulation saturation and limiters) over soft nonlinearities (such as Park's transformations and PLL) in shaping the large-signal behavior of the converter. The paper develops large-signal gains of hard nonlinearities using different types of describing functions. The paper shows that the large-signal impedance of a VSC can be shaped to reduce resonance-generated distortions by inserting limiters in the control system of the VSC. Developed large-signal impedance models are validated using numerical simulations of a VSC with dq current control and PLL. In conclusion, a large-signal impedance measurements of a commercial 1 MW VSC-based inverter and a medium-voltage doubly-fed induction generator with approximate 4 MW rating are presented to experimentally demonstrate the influence of the injected perturbation magnitude on the impedance response.
Here a study in optimal dispatch and economic analysis of a novel nuclear hybrid energy system (NHES) with large-scale hydrogen storage and a novel control scheme is conducted. The control scheme makes charge and discharge decisions by using the real-time electricity price relative to the historical price distribution. The pricing data is taken from the ERCOT Houston and West load zones with different price oscillations. Six case control studies with different levels of aggressiveness were chosen for each load zone for a total of 12 case studies. It is found that in a high price volatility load zone, a more aggressive control strategy maximizes revenue, while in a less oscillatory load zone, a moderate control strategy performs better. The NHES can store energy when the price is low and sell additional electricity when the price is high, as well as participate in the ancillary services market. Due to these advantages, the NHES can generate 10–40 million USD more revenue annually than a stand-alone nuclear plant. Due to higher costs, the NHES has a higher LCOE (81.36 USD/MWh) than a stand-alone plant (68.66 USD/MWh); however, the LCOE of the NHES is still comparable to other new forms of electricity generation. It is found that both the NHES and the stand-alone plant are not economical in the existing electricity market. Due to the extra revenue generated, the hybrid system has a positive annual cashflow whereas the stand-alone plant does not. It is found that the hybrid plant needs less cost subsidy than a stand-alone plant to become economical.
This work aims at bringing advances in discrete optimization algorithms to solving practical engineering problems at scale. Often times, in many engineering design problems, there is a need to select a small set of influential or representative elements from a large ground set of entities in an optimal fashion. Submodular optimization provides for a formal way to solve such problems. Common examples with infrastructure systems involve sensor placement and identification of key entities with certain objectives. However, scaling these approaches to large infrastructure systems can be challenging because of the high computational complexity of the overall framework that include the optimization algorithms as well as high-complexity compute-oracles that provide the necessary objective function values. In this work, we explore a well-studied and widely-applicable paradigm, namely leader-selection in a multi-agent networked setting in the context of scalable methodologies. We demonstrate novel frameworks that utilize variations of accelerated submodular optimization algorithms along with linear-algebraic methods that can help accelerate the oracle computations. We further explore this combination in conjunction with graph partitioning paradigms to take advantage of the accelerated algorithms in a distributed setting. Finally we demonstrate the key findings on a practical problem in an operational setting. For this, we leverage an example road network with approximately 18k nodes and 27k edges in a traffic control application, where we seek a limited number of k=200 key intersections. This problem can be solved in a serial setting in just under 5 hours providing more than 2 orders of magnitude speed-up over methods that do not consider acceleration techniques.
At a large Department of Energy-owned (DOE) site, there are challenges to communicating Environmental Management System (EMS) topics effectively. With multiple contractors and Environmental Management System scopes, as well as a large number of employees, communication preferences and possibilities vary, providing both the benefit and the challenge of differing pathways for sharing information. Additionally, data collection for site-wide environmental reporting involves numerous points of contact spread across contractors and requires organization and integrated communication. Focusing on the value of communication to enhance EMS education and awareness to drive environmental performance, we discuss the communication methods used both at a site-wide level and by individual organizations. Example methods include site-wide working group meetings, internal Share Point, site-wide surveys, collaborative reporting, weekly newsletters, and combined communication efforts with the Integrated Safety Management System (ISMS). Using external audit results to gauge employee environmental awareness and culture, we analyze the effectiveness of EMS communications. In conclusion, integration of EMS communication in alignment with the ISMS has assisted in meeting International Organization of Standardization 14001 (ISO 14001) requirements and strengthened the concept that environmental protection is part of safety for workers and the site. Increased environmental enthusiasm and awareness supports the effectiveness of EMS communication methods and positive external audit results. These results benefit other sites with EMS to gain knowledge of integrated communication efforts that increase the effectiveness of the EMS, environmental performance, and conformance with ISO 14001. By assessing the effectiveness of actual EMS communication methods, contractors will be able to take away tools to enhance environmental communication in their workplace. (authors)
Single photon emission computed tomography (SPECT) scanner using cadmium zinc telluride (CZT) offers improved imaging capability over conventional NaI (Tl)-based SPECT scanner. We aim to demonstrate a full-ring SPECT system design with eight large-area CZT detectors that can be used for a broad spectrum of SPECT radiopharmaceuticals and provides higher sensitivity and better spatial resolution than those of conventional NaI (Tl)-based gamma cameras. A newly-designed full-ring SPECT system is composed of 8 large-area CZT cameras (128 mm × 179.2 mm effective area) that can be independently swiveled around their own axes of rotation independently and can have radial motion for varying aperture sizes that can be adapted to different sizes of imaging volume. Extended projection data were generated by conjoining projections of two adjacent detectors to overcome the limited field-of-view (FOV) by each CZT camera. Using Monte Carlo simulations, we evaluated this new system design with digital phantoms including a Derenzo hot-rod phantom and a Zubal brain phantom. Comparison of performance metrics such as spatial resolution, sensitivity, contrast-to-noise ratio (CNR), and contrast-recovery ratio were made between our design and a conventional SPECT scanner. The proposed scanner could result in up to about 3 times faster in acquisition time over conventional scan time at same acquisition time per step. The spatial resolution of our proposed scanner was similar or better to that of the conventional scanner, and there was significant performance improvement over the conventional scanner particularly in sensitivity (approximately 4 times). Overall, we successfully reconstructed the phantom image for both 99 mTc-based perfusion and 123 I-based dopamine transporter (DaT) brain studies simulated for our new design. In particular, the striatal/background contrast-recovery ratio in 3-to-1 reference ratio was over the 0.8 for the 123 I-based DaT study. In conclusion, we demonstrated the potential of our new full-ring CZT SPECT design, showing improved performance metrics such as improved system sensitivity and CNR while maintaining other important imaging parameters such as spatial resolution.
Today’s High Performance Computing (HPC) systems contain thousand of nodes which work together to provide performance in the order of petaflops. The performance of these systems depends on various components like processors, memory, and interconnect. Among all, interconnect plays a major role as it glues together all the hardware components in an HPC system. A slow interconnect can impact a scientific application running on multiple processes severely as they rely on fast network messages to communicate and synchronize frequently. Unfortunately, the HPC community lacks a study that explores different interconnect errors, congestion events and applications characteristics on a large-scale HPC system. In our previous work, we process and analyze interconnect data of the Titan supercomputer to develop a thorough understanding of interconnects faults, errors, and congestion events. In this work, we first show how congestion events can impact application performance. We then investigate application characteristics interaction with interconnect errors and network congestion to predict applications encountering congestion with more than 90% accuracy.
Historically, distribution system planning studies mainly focused on steady state and quasi-steady state analysis, with limited attention paid to dynamic analysis. This paper develops three-phase, electromechanical models for both grid-forming and grid-following inverters, and integrates them into an open source, three-phase distribution network solver, thereby enabling dynamic simulation of large-scale, three-phase unbalanced distribution systems with high penetration of inverter-based DERs. The proposed inverter models are validated against electromagnetic simulation and field test data from the CERTS/AEP microgrid testbed, and simulated in an islanded 5252 node distribution system in the GridLAB-D simulation environment. Simulation verifies the effectiveness of the proposed inverter models for large-scale distribution system analysis. Finally, study results show that compared to traditional grid-following inverters, the high penetration of grid-forming inverters can improve the voltage and frequency stability of islanded distribution systems.
We report APW+lo (augmented plane wave plus local orbital) density functional theory (DFT) calculations of large molecular systems using the domain specific SIRIUS multi-functional DFT package. The APW and FLAPW (full potential linearized APW) task and data parallelism options and the advanced eigen-system solver provided by SIRIUS can be exploited for performance gains in ground state Kohn–Sham calculations on large systems. This approach is distinct from our prior use of SIRIUS as a library backend to another APW+lo or FLAPW code. We benchmark the code and demonstrate performance on several magnetic molecule and metal organic framework systems. We show that the SIRIUS package in itself is capable of handling systems as large as a several hundred atoms in the unit cell without having to make technical choices that result in the loss of accuracy with respect to that needed for the study of magnetic systems.