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This is the final report for the UW-Madison efforts on the PIPER Performance Insight for Programmers and Exascale Runtimes research project.
Project Objectives: To develop a new class of advanced, cost competitive aluminum casting alloys providing a 25% improvement in component strength relative to components made with A319 or A356 alloys using sand and semi-permanent casting processes for high-performance engine applications. To demonstrate the power of Integrated Computational Materials Engineering (ICME) tools for accelerating the development of new materials and processing techniques, as well as to identify the gaps in ICME capabilities. To develop comprehensive cost models to ensure that components manufactured with these new alloys do not exceed 110% of the cost using incumbents alloys A319 or A356. To develop a technology transfer and commercialization plan for deployment of these new alloys in automotive engine applications. The key targets and baseline are shown in the table below.
There are three research reactors in the world having fuel plates curved as circle-involute (a spiral generated around a circle): The Oak Ridge National Laboratory (ORNL) High Flux Isotope Reactor (HFIR) located in Tennessee, U.S.A. [ORNL, 2018]; The Laue-Langevin Institute (ILL) High Flux Reactor (RHF) located in Grenoble, France [ILL, 2018]; and, The Technical University of Munich (TUM) Research Neutron Source Heinz Maier-Leibnitz (FRM II) located in Garching, Germany [TUM, 2018]. All three reactors are currently using Highly Enriched Uranium (HEU, 235U/U ≥ 20 wt. %) as fuel and all three are actively engaged in activities to convert to Low Enriched Uranium (LEU, 235U/U < 20 wt. %) fuel. More information on these reactors can be found in Section two. For various reasons, these reactors have expressed interest in using Computational Fluid Dynamics (CFD) tools to perform their Steady-State Thermal-Hydraulic (SSTH) safety calculations. Using CFD tools for SSTH analysis represents generally a significant departure from traditional methods and requires thorough verification and validation (V&V) to be accepted by regulators. This is why Argonne National Laboratory (ANL) and the involute reactors formed an informal group to help each other in this endeavor. This so-called Involute Working Group (IWG) aims at supporting the qualification of CFD tools for SSTH safety calculations. Activities include benchmarking, code-to-code comparison, Verification and Validation (V&V) as well as technical support. More information on the IWG and the reasons why involute-plate reactors are interested in CFD can be found in Section three. The present study aims at testing three turbulence models commonly implemented in commercial software (namely K-Epsilon, K-Omega and Reynolds-Stress) and assessing their relevance for involute-plate reactor application. An experiment performed by Gambill and Bundy in 1961 was performed to measure heat transfer coefficients in conditions prototypic of the HFIR reactor [Gambill, 1961]. More details on this experiment are provided in Section four. Based on the information available, CFD models of this experiment have been created and the experimental results have been compared to the ones obtained with these CFD models. CFD models and the results of this comparison are provided in Section five.
Project Objectives include the following: 1) To develop a new class of advanced, cost competitive aluminum casting alloys providing a 25% improvement in component strength relative to components made with A319 or A356 alloys using sand and semi-permanent casting processes for highperformance engine applications; 2) To demonstrate the power of Integrated Computational Materials Engineering (ICME) tools for accelerating the development of new materials and processing techniques, as well as to identify the gaps in ICME capabilities; 3) To develop comprehensive cost models to ensure that components manufactured with these new alloys do not exceed 110% of the cost using incumbent alloys A319 or A356; 4) To develop a technology transfer and commercialization plan for deployment of these new alloys in automotive engine applications; 5) The key targets and baseline are shown in the table below.
Scientific workflows have become integral tools in broad scientific computing use cases. Science discovery is increasingly dependent on workflows to orchestrate large and complex scientific experiments that range from the execution of a cloud-based data preprocessing pipeline to multi-facility instrument-to-edge-to-HPC computational workflows. Given the changing landscape of scientific computing (often referred to as a computing continuum) and the evolving needs of emerging scientific applications, it is paramount that the development of novel scientific workflows and system functionalities seek to increase the efficiency, resilience, and pervasiveness of existing systems and applications. Specifically, the proliferation of machine learning/artificial intelligence (ML/AI) workflows, need for processing large-scale datasets produced by instruments at the edge, intensification of near real-time data processing, support for long-term experiment campaigns, and emergence of quantum computing as an adjunct to HPC, have significantly changed the functional and operational requirements of workflow systems. Workflow systems now need to, for example, support data streams from the edge-to-cloud-to-HPC, enable the management of many small-sized files, allow data reduction while ensuring high accuracy, orchestrate distributed services (workflows, instruments, data movement, provenance, publication, etc.) across computing and user facilities, among others. Further, to accelerate science, it is also necessary that these systems implement specifications/standards and APIs for seamless (horizontal and vertical) integration between systems and applications, as well as enable the publication of workflows and their associated products according to the FAIR principles.
This final report documents cost analysis conducted for the Department of Energy over a five year period (2016 to 2021) pertaining to hydrogen production and delivery system components, focusing on the key remaining challenges of the technology pathways within the Hydrogen Production and Delivery sub-program portfolio. A particular focus was placed on electrolysis for the generation of hydrogen. The effort primarily used the H2A discounted cash flow computational model as a tool to project hydrogen cost ($/kgH 2 ) and determine status improvements resulting from technology advancements. The effort also considered cost as a function of production volume, employed error bars to illustrate uncertainties in the cost estimates, and utilized sensitivity analyses to show the potential for cost reductions. The project examined a range of hydrogen production and delivery related systems. These included WireTough wire-wrapped pressure vessels for hydrogen storage, proton exchange membrane (PEM) electrolysis, solid oxide electrolysis (SOE), anion exchange membrane (AEM) electrolysis, photoelectrochemical (PEC) electrolysis, solar thermochemical hydrogen (STCH) production, the cost of energy transmission, and a study on the necessary price of hydrogen to produce competitively-priced electricity via fuel cell conversion.
Accumulation of soils and other particulate matter on the front cover glass of solar photovoltaic (PV) modules results in transmission losses that detrimentally affect the power output of PV installations. The conventional solution to this problem is manual abrasive scrubbing of modules, which entails significant water usage and manpower. To further combat this issue, there is a concerted effort within the PV industry to develop anti-soiling (AS) coatings to mitigate power losses due to soiling of PV modules, which can exceed 35% in some cases. However, relatively little is known about the fundamental physical and chemical mechanisms that enable anti-soiling behavior. In this project, a combination of advanced X-ray analysis tools and first principles computational modeling has employed to understand the physical and chemical interactions between environmental soils and PV cover glass materials. The specific objectives were: 1) investigate soiling interactions and cementation behavior of relevant PV materials, including bare glass, conventional antireflective (AR) coatings, and a commercial AS coating, using a library of representative particulate soils, and 2) utilize first principles computational spectroscopy modeling to interpret the experimental X-ray spectroscopy measurements and determine the detailed surface chemistry changes that occur on these surfaces in the presence of soiling and cementation.
ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic and electromagnetic simulation capabilities. ANSYS LS-DYNA is the most used explicit simulation program capable of simulating the response of materials to short periods of severe loading. Its many elements, contact formulations, material models, and other controls can be used to simulate complex models with control over all the details of the problem. ANSYS LS-DYNA has a vast array of capabilities to simulate extreme deformation problems using its explicit solver. Engineers can tackle simulations involving material failure and look at how the failure progresses through a part or through a system. Models with large amounts of parts or surfaces interacting with each other are also easily handled, and the interactions and load passing between complex behaviors are modeled accurately. Using computers with higher numbers of CPU cores can drastically reduce solution times. In addition, many consulting firms and hundreds of universities use ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. ANSYS has successfully passed over 100 customer quality system audits against American Society of Mechanical Engineers (ASME) NQA-1 and 10 CFR Part 50, Appendix B, since the company was founded, over 60 of which have been since 1997. ANSYS has successfully passed over 100 International Organization for Standardization (ISO) 9001 assessments. ANSYS design analysis software is the first created within a quality system with ISO 9001 certification, which is the internationally accepted quality standard. Product development, testing, maintenance, and support processes also meet the US Nuclear Regulatory Commission’s (NRC’s) quality requirements, as they have for nearly four decades. ANSYS staff perform more than 60,000 software verification tests before releasing each new product. ASME NQA-1-2012 (Subpart 2.7 is specific to software) is the industry- and NRC-accepted approach (consensus standard) for meeting 10 CFR Part 50, Appendix B, requirements.
The Final Technical Report describes a multi‑institution effort to develop programmable molecular qubits as precision quantum sensors for probing quantum materials. The team created chemically tunable qubits with optical addressability and practical coherence, integrated them into thin films and frameworks while preserving functionality, and established new magnetic and electric sensing methods suited to two‑dimensional magnets, ferroelectrics, and multiferroics. They also built computational models and spectroscopic tools that connect molecular design to material behavior, enabling access to quantum phenomena that previously could not be measured. The project produced more than 40 publications and trained a large cohort of graduate students and postdocs, strengthening the workforce and infrastructure needed for DOE's quantum information science mission.
This dataset contains acoustic propagation model outputs, computational subroutines, and analysis tools for underwater sound propagation in the Block Island region, including parabolic equation (PE) model results, visualization products, and comprehensive modeling software tools.
Current mid-fidelity modeling approaches for floating offshore wind turbines (FOWTs) have been found to underpredict the nonlinear, low-frequency wave excitation and the response of semisubmersible FOWTs. To examine the cause of this underprediction, the OC6 project is using computational fluid dynamics (CFD) tools to investigate the wave loads on the OC5-DeepCwind semisubmersible, with a focus on the nonlinear difference-frequency excitation. This paper focuses on assessing the uncertainty of the CFD predictions from simulations of the semisubmersible in a fixed condition under bichromatic wave loading and on establishing confidence in the results for use in improving mid-fidelity models. The uncertainty for the nonlinear wave excitation is found to be acceptable but larger than that for the wave-frequency excitation, with the spatial discretization error being the dominant contributor. Further, unwanted free waves at the difference frequency have been identified in the CFD solution. A wave-splitting and wave load-correction procedure are presented to remove the contamination from the free waves in the results. A preliminary comparison to second-order potential-flow theory shows that the CFD model predicted significantly higher difference-frequency wave excitations, especially in surge, suggesting that the CFD results can be used to better calibrate the mid-fidelity tools.
In this paper, a new version of the FLOw Redirection and Induction Dynamics (FLORIDyn) model is presented. The new model uses the three-dimensional parametric Gaussian FLORIS model and can provide dynamic wind farm simulations at a low computational cost under heterogeneous and changing wind conditions. Both FLORIS and FLORIDyn are parametric models which can be used to simulate wind farms, evaluate controller performance and can serve as a control-oriented model. One central element in which they differ is in their representation of flow dynamics: FLORIS neglects these and provides a computationally very cheap approximation of the mean wind farm flow. FLORIDyn defines a framework which utilizes this low computational cost of FLORIS to simulate basic wake dynamics. This is achieved by creating so-called observation points (OPs) at each time step at the rotor plane which inherit the turbine state. In this work, we develop the initial FLORIDyn framework further considering multiple aspects. The underlying FLORIS wake model is replaced by a Gaussian wake model. The distribution and characteristics of the OPs are adapted to account for the new parametric model but also to take complex flow conditions into account. To achieve this, a mathematical approach is developed to combine the parametric model and the changing, heterogeneous world conditions and link them with each OP. We also present a computationally lightweight wind field model to allow for a simulation environment in which heterogeneous flow conditions are possible. FLORIDyn is compared to Simulator for Offshore Wind Farm Applications (SOWFA) simulations in three- and nine-turbine cases under static and changing environmental conditions. The results show a good agreement with the timing of the impact of upstream state changes on downstream turbines. They also show a good agreement in terms of how wakes are displaced by wind direction changes and when the resulting velocity deficit is experienced by downstream turbines. A good fit of the mean generated power is ensured by the underlying FLORIS model. In the three-turbine case, FLORIDyn simulates 4 s simulation time in 24.49 ms computational time. The resulting new FLORIDyn model proves to be a computationally attractive and capable tool for model-based dynamic wind farm control.
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Researchers and engineers at the National Wind Technology Center have developed a wide range of computer modeling and simulation tools to support the wind and water power industries with state-of-the-art design and analysis capabilities.
The development of Application Specific Integrated Circuits (ASIC) for pixel detectors with complex in-pixel processing using Computer Aided Design (CAD) tools that are, themselves, mainly developed for the design of conventional digital circuits requires a specialized approach. Mixed signal pixels often require parasitically aware detailed analog front-ends and extremely compact digital back-ends with more than 1000 transistors in small areas below 100μm x 100μm. These pixels are tiled to create large arrays, which have the same clock distribution and data readout speed constraints as in, for example, micro-processors. The methodology uses a modified mixed-mode on-top digital implementation flow to not only harness the tool efficiency for timing and floor-planning but also to maintain designer control over compact parasitically aware layout.
The analysis tool employs a computer-implemented algorithm that uses homotopy-based approaches to map the solution from the exit point to the controlling unstable equilibrium point (UEP). The computational time is reduced significantly by using an approximate exit point rather than computing an accurate exit point as it is required in finding the controlling UEPs using traditional transient stability direct methods. In addition, this method eliminates the necessity of computing the minimum gradient point (MGP) which is a key element in using Newton methods. These properties provide an advantage to homotopy-based approaches over traditional iterative methods in terms of both speed of computation and reliability of finding solutions.
The paper discusses the modeling and simulations of Deteriorated Turbulent Heat Transfer (DTHT) for a wall-heated fluid flows, which can be observed in gas-cooled nuclear power reactors during Pressurized Conduction Cooldown (PCC) event due to loss of force circulation flow. The DTHT regime is defined as the deterioration of normal turbulent heat transport due to increase of acceleration and buoyancy forces. The Computational Fluid Dynamics (CFD) tools such as Nek5000 and STAR-CCM+ can help to analyze the DTHT phenomena in reactors for efficient thermal-fluid designs. 3D CFD non-isothermal modeling and simulations were performed in a wall-heated circular tube. The simulation results were verified with two different CFD tools, Nek5000 and STAR-CCM+, and validated with an experimental data. The predicted bulk temperatures were identical in both CFD tools, as expected. Good agreement between simulated results and measured data were obtained for wall temperatures along the tube axis using Nek5000. In STAR-CCM+, the under-predicted wall temperatures were mainly due to higher turbulence in the wall region. In STAR-CCM+, the predicted DTHT was over 48% at outlet when compared to inlet heat transfer values.
A well-designed thermal management system is critical to the life and performance of electric-drive vehicles (EDVs) hybrids (HEVs), plug-in hybrids (PHEVs), and all-electric vehicles (EVs). Temperature and temperature uniformity both significantly affect the performance, lifespan, and safety of vehicle energy storage devices. NREL conducts thermal management research and development (R&D) to optimize battery performance and extend useful life. A recognized leader in battery thermal analysis and characterization, NREL evaluates electrical and thermal performance of battery cells, modules, and packs, full energy storage systems, and the interaction of these systems with other vehicle components. The lab's performance assessments factor in the design of the thermal management system, the thermal behavior of the cell, battery lifespan, and safety of the energy storage system, as well as full integration into a vehicle. The lithium-ion (Li-ion) batteries found in most of today's electric-drive vehicles are smaller and more lightweight than previous nickel-metal hydride (NiMH) technology, but they are also more sensitive to overheating, overcharging, and extreme spikes in temperature known as thermal runaway. High temperatures diminish battery life and increase battery replacement costs, while low temperatures decrease battery power and capacity, all of which impact vehicle range, performance, and affordability. NREL's breakthrough research is focused on reducing thermal barriers to achieve more uniform temperatures. NREL uses its R&D 100 Award-winning Isothermal Battery Calorimeters, the only instruments in the world capable of such precise thermal measurements, for much of this research. Calorimeter readings are paired with thermal imaging of batteries using infrared cameras to evaluate battery temperature distribution. In addition, NREL is working with industry to develop computer-aided engineering software tools to optimize thermal management of batteries. NREL's analysis for the U.S. Advanced Battery Consortium (USABC) show that optimized thermal management can increase battery power by more than 10%. Without proper thermal management, an EDV battery can last more than 10 years in a temperate climate, like in Minnesota, but only 7 years in a hot climate, such as in Arizona. In extreme instances, battery overheating can pose safety hazards, including fires. Performance: Maintaining desired temperature ranges is critical in optimizing EDV battery storage capacity, lifespan, and performance, and eventually impacts cost and consumer acceptance. NREL's breakthrough research focuses on achieving more uniform temperatures while a vehicle is in motion and actively generating heat, as well as when it is parked and exposed to ambient temperatures over prolonged periods of time. Safety: Most energy storage systems deliver maximum performance at higher temperatures. However, this extreme heat can overload systems and create dangerous conditions. NREL evaluation helps to more effectively regulate thermal characteristics, providing greater safeguards and stronger performance. NREL has invented a device that emulates internal short circuits in batteries to better understand how to prevent future failures and related hazards.