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At least 1,549 records · Page 86

Understanding the I/O Performance Gap Between Cori KNL and Haswell

The Cori system at NERSC has two compute partitions with different CPU architectures: a 2,004 node Haswell partition and a 9,688 node KNL partition, which ranked as the 5th most powerful and fastest supercomputer on the November 2016 Top 500 list. The compute partitions share a common storage configuration, and understanding the IO performance gap between them is important, impacting not only to NERSC/LBNL users and other national labs, but also to the relevant hardware vendors and software developers. In this paper, we have analyzed performance of single core and single node IO comprehensively on the Haswell and KNL partitions, and have discovered the major bottlenecks, which include CPU frequencies and memory copy performance. We have also extended our performance tests to multi-node IO and revealed the IO cost difference caused by network latency, buffer size, and communication cost. Overall, we have developed a strong understanding of the IO gap between Haswell and KNL nodes and the lessons learned from this exploration will guide us in designing optimal IO solutions in many-core era.

97 MATHEMATICS AND COMPUTING↗

Fundamental Advancements in Pre-Chamber Spark Ignition and Emissions Control for Natural Gas Engines

Argonne National Laboratory, the National Renewable Energy Laboratory, Oak Ridge National Laboratory, and Sandia National Laboratories collaborated on research to address barriers for natural gas engine efficiency. This research project focuses on early stage research focusing on pre-chamber spark-ignition (PCSI) to achieve diesel-like efficiency in medium- and heavy-duty natural gas engines by extending the lean dilution limit and/or exhaust gas recirculation (EGR) dilution limit, as well as shortening burn duration, with integrated aftertreatment. This project integrates experimental and simulation based tasks to address four key barriers to market penetration of PCSI for medium- and heavy-duty natural gas engines. These include Inadequate science base and simulation tools to describe/predict the fluid-mechanical and chemical-kinetic processes governing PCSI to enable engineers in industry to optimize designs for efficiency, noise, reliability, pollutant formation, emissions control integration, and drivability; limited ability to extend EGR and/or lean dilution limits at higher loads; increased propensity for PCSI hot-spot pre-ignition at high loads relative to spark ignition; and ineffective methane catalysts for the high engine-out unburned fuel concentrations coupled with low exhaust temperatures (<<400 degrees C) of high efficiency engines.

33 ADVANCED PROPULSION SYSTEMS↗

Multi-scale simulations of wind farm performance with complex terrain and weather events

Predicting the response of wind farms to local weather is necessary for optimal design and operation. In this work, simulation and analysis of a frontal passage through a utility scale wind farm is achieved for the first time using a seamless multi-scale modeling approach. A generalized actuator disk (GAD) wind turbine model is used to represent turbine wakes, and results are compared to novel radar observations during the frontal passage. The Weather Research and Forecasting (WRF) model is employed with a nested grid setup that allows for coupling between multi-scale atmospheric conditions and turbine response. Starting with mesoscale forcing, the atmosphere is dynamically downscaled to the region of interest, where the interaction between turbulent flows and individual wind turbines is simulated with the GAD at10 m resolution. Several improvements are made to the GAD model to mimic realistic turbine operation, including a yawing capability and a power output calculation. Ultimately, the model is able to capture both the dynamics of the frontal passage and the turbine response; predictions show good agreement with observed turbine wake structure, velocity deficit, and power output after accounting for a phase shift in the mesoscale forcing. This study demonstrates the utility of the WRF-GAD framework for simulating wind farm performance under complex atmospheric conditions.

17 WIND ENERGY↗

Kinetics Modeling for Design of Continuous Enzymatic Hydrolysis

Enzymatic hydrolysis of cellulose to monomeric sugars continues to be a limiting step in cost-effectively producing sugar and fermentation-based biofuels from biomass. In particular, the high cost of enzymes coupled with the long time-scale of reaction pose challenges to economic viability. Performing enzymatic hydrolysis in a continuous mode with enzyme recycle may provide a path towards substantially reduced costs for sugar production, but design and analysis are complicated by a lack of suitable kinetics models. Computationally attainable models, such as fractal-based models, require knowledge of the reaction-history of the biomass, and are thus only suitable for describing the batch reactions from which they are derived. Fundamental models, while potentially more generalizable, are often too computationally intensive to use in process or reactor modeling. In this work, a phenomenological rate model is proposed based on a two-phase substrate representation. Good agreement is seen between batch and continuous enzymatic hydrolysis (CEH) experiment data, which validates the model and enables us to solve for reactor design parameters, such as CEH reactor size and stream flow rates, based on process variables like yield. This model is integrated with techno-economic analysis software to explore economic sensitivities. Important design optimizations and tradeoffs are identified and quantified, including the relative cost imposed by rate slowdown from sugar inhibition versus the cost to remove and concentrate sugars at a lower concentration. It also identifies, high-leverage avenues for further exploration, such as increasing the maximum feasible solids concentration, and sustaining high membrane flux and reliability.

09 BIOMASS FUELS↗

A Novel High Energy Density Sorption-based Thermal Battery for Low-grade Thermal Energy Storage

Thermal energy storage (TES) can alleviate peak demand on the electricity grid by offsetting building thermal loads, increasing the grid’s reliability and resilience. However, low energy density and poor energy performance of existing TES technologies limit their applications. Sorption-based thermal battery (STB) system is thus developed using three-phase sorption technology to harvest low-temperature heat, store it with a much higher energy density than common TES systems and dehumidify air or provide space cooling in buildings. Although STB has been experimentally proved to be feasible, influencing factors on its performance are still unknown by far. Therefore, this paper conducted a parametric analysis on crystallization and crystal dissolution performance of a developed STB test rig. The crystallization results showed that the energy density of the STB increased with reducing the solution flow rate and the cooling water temperature. The dissolution results showed that a higher discharge rate of the STB can be achieved with increasing the flow rate and temperature of inlet diluted solution. The work in this study is helpful to the optimal design and operation of the STB system.

Wang, Lingshi↗

Integration of Dynamical System Scaling to RAVEN and Facility Application

As part of the design optimization and model validation effort within the hybrid energy systems program, the research to implement dynamical system scaling (DSS) code to RAVEN is funded under the Integrated Energy System program in collaboration with the Digital Reactor Technology & Development department. The DSS data processing algorithm has been coded within the RAVEN framework along with other metrics and postprocessing models. The implemented code was tested using a gravity-driven draining tank draining case modeled in RELAP5-3D and generated data was successfully postprocessed based on the scaling analyses defined by DSS. Postprocessed data concluded less agreement for the tank exit velocity and indicated that the modeled input deck for RELAP5-3D requires modification to enforce minimal pressure differential effects to the draining process.

97 MATHEMATICS AND COMPUTING↗

Recent Advances in Analysis and Design of Axial Flux Permanent Magnet Electric Machines

Axial flux permanent magnet machines (AFPM) are popular for applications that benefit from high torque density and an axially compact form factor, such as in-wheel traction drives. Although the radial flux permanent magnet machine (RFPM) and the AFPM work based on the same underlying principle, the differences in their geometry introduce complexities in analysis of the AFPM. In this paper, the different AFPM design variants, their sizing approaches, computationally efficient design optimization techniques, and manufacturing techniques reported in literature are reviewed. In addition to classical AFPM machines, emerging variants and research opportunities with potential to push the boundaries of electric machine technology are reviewed. These include bearingless AFPMs, magnetically geared AFPMs, and combined radial-axial flux machines.

Nishanth, FNU↗

Optimal Decision Making in High-Throughput Virtual Screening Pipelines

ABSTRACT Effective selection of the potential candidates that meet certain conditions in a tremendously large search space has been one of the major concerns in many real-world applications. In addition to the nearly infinitely large search space, rigorous evaluation of a sample based on the reliable experimental or computational platform is often prohibitively expensive, making the screening problem more challenging. In such a case, constructing a high-throughput screening (HTS) pipeline that pre-sifts the samples expected to be potential candidates through the efficient earlier stages, results in a significant amount of savings in resources. However, to the best of our knowledge, despite many successful applications, no one has studied optimal pipeline design or optimal pipeline operations. In this study, we propose two optimization frameworks, applying to most (if not all) screening campaigns involving experimental or/and computational evaluations, for optimally determining the screening thresholds of an HTS pipeline. We validate the proposed frameworks on both analytic and practical scenarios. In particular, we consider the optimal computational campaign for the long non-coding RNA (lncRNA) classification as a practical example. To accomplish this, we built the high-throughput virtual screening (HTVS) pipeline for classifying the lncRNA. The simulation results demonstrate that the proposed frameworks significantly reduce the effective selection cost per potential candidate and make the HTS pipelines less sensitive to their structural variations. In addition to the validation, we provide insights on constructing a better HTS pipeline based on the simulation results.

97 MATHEMATICS AND COMPUTING↗

Bonded Interfaces for High-Temperature Power Electronics

Wide-bandgap devices have pushed the operational limit of semiconductor devices in automotive power electronics packages to higher temperatures (>200 degrees C). While a higher efficiency can be achieved through the use of wide-bandgap devices, the entire package must be re-designed with components that can withstand the higher temperature limits. Sintered silver and transient liquid phase bonds are potential candidates as bonded materials for use in higher temperatures however, the underlying mechanics of deformation under thermal loads and the resulting failure mechanisms in these materials are not well understood. Furthermore, thermomechanical modeling plays a key role in understanding the degradation behavior of bonded interface materials and for design optimization of power electronics packages.

ADVANCED PROPULSION SYSTEMS,DIRECT ENERGY CONVERSI↗

GradientGraph

Under this SBIR Phase II, Reservoir Labs has developed G2 Analytics, a new technology that allows network operators to analyze bottleneck and flow performance with high precision. G2 delivers a new analytical approach and framework to resolve a variety of key problems found in modern communication networks, including: traffic engineering, routing, flow scheduling, network design, capacity planning, resiliency analysis, network slicing, or service level agreement (SLA) management, among others. G2 leverages the bottleneck structure of congestion-controlled communication networks, a recent mathematical discovery by the Reservoir team [RL19b, RL20a, RL20b, RL21a]. Bottleneck structures reveal how perturbations on flows and links propagate through the network, providing an analytical framework to measure (qualitatively and quantitatively) the ripple effects induced as they traverse the network. Leveraging the mathematics of bottleneck structures, Reservoir Labs is developing the G2 technology to provide network operators with a framework to design, optimize and troubleshoot network performance. This delivery includes the G2 software stack.

Yellamraju, Sruthi↗

Sensitivity Coefficients Calculated for the Prompt Neutron Decay Constant At or Near Delayed Critical

The derivation of a non-invasive prompt neutron decay constant sensitivity coefficient is provided in this work. The computation of the sensitivity coefficient derived in this work does not require modification of Monte Carlo source code and is based on capabilities available in Monte Carlo N-Particle R© Code Version 6.2. The prompt neutron decay constant sensitivity coefficients are calculated for 44-group and 252-group energy structures for specific nuclide-reaction pairs in the Jezebel benchmark experiment. The nuclide-reaction pairs investigated in this work include Pu- 239(n,f), Pu-240(n,f), and Pu-241(n,f). Physical explanations of the sensitivity profiles exhibited by the 252-group energy structure are investigated for the prompt neutron multiplication factor, mean neutron lifetime, and prompt neutron decay constant. The prompt neutron decay constant sensitivity coefficients calculated for the 44-group and 252-group energy structure of Pu-239(n,f) are compared. Lastly, the 44-group energy structure sensitivity coefficients calculated are used for nuclear-data induced uncertainty quantification of the neutron multiplication factor. This work shows that a reduction in the nuclear data-induced uncertainty of the neutron multiplication factor is possible for all nuclide-reaction pairs investigated when prompt neutron decay constant sensitivity coefficients are utilized. This is important for new critical experiment design optimization studies of measurement configurations. This work provides a basis for more detailed sensitivity analysis and uncertainty quantification of nuclide, reaction, and energy-specific cross section data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Reactivity Coefficient Measurements and Sensitivity Studies [Abstract]

Nuclear data validation is often performed today using criticality measurements. The gold standard for criticality measurements is the International Criticality Safety Benchmark Experiment Project (ICSBEP). The validation specifically focuses on the effective multiplication factor (k eff ). K eff is a relatively easy parameter to infer and has reduced uncertainty due to being at or above critical. However, while k eff is a well-documented parameter with detailed sensitivity and uncertainty analysis, it cannot be used as a standalone metric to determine inaccuracies in nuclear data (e.g., cross section data, PFNS, nu), which is based on theory, physics, and differential measurements. The Experiments Underpinned by Computational Learning for Improvements in nuclear Data (EUCLID) project aims to identify compensating errors in specific nuclear data by optimally designing experiments that are sensitive to a suite of measurement parameters beyond k eff . By identifying how each parameter's nuclear data sensitivity differs from others, experiments can be designed to constrain questionable nuclear data. One sensitivity that is of particular interest to this project includes reactivity coefficient sensitivities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Common Cause Failure Evaluation of High Safety-significant Safety-related Digital Instrumentation and Control Systems

Digital instrumentation and control (DI&C) systems in nuclear power plants (NPPs) have many advantages over analog systems but also pose different engineering and technical challenges, such as potential threats due to common cause failures (CCFs). This paper proposes a Platform for Risk Assessment of DI&C (PRADIC) developed by Idaho National Laboratory for dealing with potential software CCFs in DI&C systems of NPPs. The methodology development of PRADIC on the quantitative evaluation of software CCFs in high safety-significant safety-related DI&C systems in NPPs is illustrated in this paper. In PRADIC, qualitative hazard analysis and quantitative reliability and consequence analysis are successively implemented to obtain quantitative risk information, compare with respective risk evaluation acceptance criteria, and provide suggestions for risk reduction and design optimization. A comprehensive case study was also performed and documented in this paper. Results show that PRADIC can effectively identify potential digital-based CCFs, estimate their failure probabilities, and evaluate their impacts to system and plant safety.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

TCR Central Shutdown Rod Fine Motion Control

Transformational Challenge Reactor (TCR) is a Helium cooled 3 MWt test reactor that leverages advances in materials and manufacturing, computing, and AI in its design. Classical design of a shutdown rod uses either gravity, pneumatic, or springs to quickly release the Central Shutdown Rod (CSR) containing neutron absorber into the reactor core stopping nuclear reaction. Generally, the motor/actuator resides outside the reactor, but the motion is transmitted through a penetration into the pressure vessel. There are also designs where the control rod drive incorporates magnetic latches with coil residing outside the pressure boundary for precise position control of the rod. We are proposing a magnetic coupling to position the shutdown rod without any penetration into the pressure vessel for the entire drive length of TCR shutdown rod. Electromagnets are currently used in non-power nuclear reactors for shutdown rods, but these electromagnets are resident inside the reactor pressure vessel. This paper will describe the use of an electromagnet outside the pressure vessel to position and release the shutdown rod. A prototype was developed at ORNL to demonstrate the concept, and a design optimization of the ferritic core and material was conducted to maximize the lift force of the electromagnet. An elevated temperature testing was also performed to ensure that the system will perform under the temperature conditions inside an operating reactor.

Fountain, Eliott J.↗

Experimental Evaluation of Thermal Storage Performance of a Dual-Purpose Underground Thermal Battery

A geothermal heat pump (GHP) system is an energy-efficient building heating and cooling technology with great potential for reducing energy consumption and decarbonization. However, applications of GHP are still limited due to the high cost, of which 30% is related to the cost of installing the conventional vertical bore ground heat exchangers, which are usually installed in boreholes 60 meters deep. A dual-purpose underground thermal battery (DPUTB) has been developed to offer a low-cost ground heat exchanger with a built-in thermal storage capacity. The DPUTB innovatively integrates a shallow-bore ground heat exchanger (the outer tank), which can be installed in a borehole less than 6 m deep, with thermal energy storage (TES) (the inner tank). DPUTB has the potential to reduce the cost of a ground source heat pump system while allowing shifting the electric demand of the building served by the GHP system from peak to off-peak hours of the electric grid by charging and discharging the thermal storage. A lab-scale (1:125 in volume) DPUTB prototype was built. Phase change material (PCM) was added to increase the thermal storage capacity and maintain the supply water temperature from the TES within the desired range for direct cooling operation during the discharge period. As PCMs are critical to the TES performance of the DPUTB, this study compared the influence of different PCMs (including salt hydrate and organic PCMs) on the discharge performance of the DPUTB. The thermal State of Charge (SoC) of the DPUTB was used to compare the performance resulting from using different PCMs. Test results indicate that the organic PCM (Methyl Laurate) outperforms salt-hydrate PCMs due to a lower melting temperature and a narrower melting temperature range during the phase change process. The results of this study provide a guide for PCM selection and the optimal design of DPUTB.

Wang, Lingshi↗

Common Cause Failure Evaluation of High Safety Significant Safety-related Digital Instrumentation and Control Systems using IRADIC Technology

Digital instrumentation and control (DI&C) systems in nuclear power plants (NPPs) have many advantages over analog systems but also pose different engineering and technical challenges, such as potential threats due to common cause failures (CCFs). This paper proposes an integrated risk assessment technology for DI&C systems (IRADIC) developed by Idaho National Laboratory for dealing with potential software CCFs in DI&C systems of NPPs. The methodology development of the IRADIC technology on the quantitative evaluation of software CCFs in high safety-significant safety-related DI&C systems in NPPs is illustrated in this paper. In IRADIC, qualitative hazard analysis and quantitative reliability and consequence analysis are successively implemented to obtain quantitative risk information, compare with respective risk evaluation acceptance criteria, and provide suggestions for risk reduction and design optimization. A comprehensive case study was also performed and documented in this paper. Results show that the IRADIC technology can effectively identify potential digital-based CCFs, estimate their failure probabilities, and evaluate their impacts to system and plant safety.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Building the Case for Hybrid Energy Developments: Webinar Recording Day 1

INL, PNNL, and NREL, with support from our academic and industry partners, hosted a 2-day webinar to learn more about the benefits of hybrid energy systems, considerations for designing the right system for communities, and practical tools that can help with the design and development process. In Day 1 of this webinar, the focus was on why users might want to consider hybrid energy systems, and frameworks that could help inform design decisions for hybrid systems, including a valuation framework, resilience framework, and hybrid system design optimization framework.

14 SOLAR ENERGY↗

Implementing the Inflation Reduction Act: What We Expect and How We Might Get There

This presentation summarizes findings from three related studies: Evaluating Impacts of the Inflation Reduction Act and Bipartisan Infrastructure Law on the U.S. Power System; The Roles and Impacts of PV-Battery Hybrids in a Decarbonized U.S. Electricity Supply; and Optimal Design and Deployment of Wind-Solar Hybrids in Low-Carbon U.S. Power System. The compilation of results from these three studies indicate that the Inflation Reduction Act could drive significant deployment of variable renewable energy technologies, but the level of deployment depends on our ability to build new transmission projects (among other factors). Hybrid systems can help, to an extent, to facilitate greater shares of wind/solar with lesser amounts of transmission expansion.

Bipartisan Infrastructure Law↗