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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 973 records · Page 54

A Brief Survey on High Performance Computing Systems Power Management

This paper provides a survey of software-based power management techniques in High Performance Computing (HPC) systems. Seven existing power management and monitoring tools and frameworks are discussed. These are: Variorum, dynamic energy-performance optimizer (DEPO), Powersched, Bull Dynamic Power Optimizer (BDPO), Energy Aware Runtime (EAR), Global Extensible Open Power Manager (GEOPM), and PoLiMEr. Each of these tools is evaluated based on hardware abstraction, optimization methods, usability, and experimental validation. This survey highlights the diversity of approaches in managing energy efficiency, from vendor-neutral APIs to algorithm-driven power capping, and dynamic frequency adjustments. Given that energy requirements for large computational systems is increasing quickly, the importance of integrating these tools into existing HPC environments and the need for further research in this rapidly evolving field is also discussed.

97 - MATHEMATICS AND COMPUTING↗

A Simple Panel System to Overcome Interface Challenges for Retrofits: Preprint

Retrofitting buildings is usually an expensive and labor-intensive process. Weatherization measures can improve comfort and energy affordability to some extent, but deep energy retrofits are needed to optimize performance and comfort, and to achieve significant energy cost savings. Barriers to deep energy retrofits include a limited supply of skilled labor, different building types, planning complexity, split incentives, and a long or non-existent ROI horizon. The "Simple Panel System" (SPS) workflow developed and demonstrated in this effort streamlines deep energy retrofits by applying advanced site capture, machine learning, and mixed reality to panelized construction. The result is a one-stop, product-independent solution for rapidly scalable retrofits with the potential to reduce construction time and project costs by 50%. Soft costs are reduced by more than 66%, total costs by more than 50%, and field construction time by more than 50% - not to mention the reduction in construction waste, improvement in working conditions, and the ability to scale without an influx of skilled labor. This paper presents the SPS and the preliminary results and findings from the pilot project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluating the Impact of Off-Design CHP Performance on the Optimal Sizing and Dispatch on Hybrid Renewable-CHP Distributed Energy Resources

The maturation of distributed energy resources (DER) has prompted the exploration of their deployment in commercial building applications due to their potential to supply energy at lower costs and emissions rates compared to centralized generation. While several software tools exist for evaluating the techno-economic potential of integrated renewable energy and combined heat and power (CHP) systems for distributed generation applications, many suffer from poor accuracy in capturing off-design (part load and changes in ambient air temperature and pressure) performance characteristics of microturbines, combustion turbines, or internal combustion engines. Thus, this paper presents a methodology for integrating these off-design characteristics in the mixed-integer linear program within REopt, a hybrid DER screening tool. The economic impact of the CHP off-design performance is observed through several application studies of various hybrid system configurations in different climates. Each study indicates how CHP off-design performance influences optimal sizing and dispatch decisions and therefore overall system economic value. We observe through case studies that modeling without the off-design effects, depending on the CHP prime mover and site, can result in Net Present Value predictions of hybrid systems that can be overoptimistic in frequently hot climates (up to 52%), too conservative in frequently cold climates (up to 11%), or unaffected (+/-1%) in temperate climates. Cases also highlight several advantages of hybrid systems relative to non-hybrid systems such as total economic value and the systems' ability to mitigate potentially negative consequences attributed to off-design performance.

ambient de-rate↗

A study of the use of linear programming techniques to improve the performance in design optimization problems

This project has two objectives. The first is to determine whether linear programming techniques can improve performance when handling design optimization problems with a large number of design variables and constraints relative to the feasible directions algorithm. The second purpose is to determine whether using the Kreisselmeier-Steinhauser (KS) function to replace the constraints with one constraint will reduce the cost of total optimization. Comparisons are made using solutions obtained with linear and non-linear methods. The results indicate that there is no cost saving using the linear method or in using the KS function to replace constraints.

Young, Katherine C.↗

Multiphysics simulations of Self-Regulating performance of an optimized molten metal fuel microreactor design

Advanced microreactors are expected to play an indispensable role in reliable energy solutions for civilian/ military applications in off-grid regions and space applications such as power supplies for Lunar and Mars bases. An innovative fast neutron spectrum heat pipe microreactor (HP-MR) concept was recently proposed with two unique features: molten U-Mn fuel and heat pipes as the heat removal mechanism. The microreactor was designed to be self-regulated, solely relying on reactivity feedbacks from fuel temperature. The reactor design has been further optimized to provide sufficient engineering safety margin and effective heat removal. In this study, the self-regulating performance of the optimized molten metal fuel microreactor was investigated by multi-physics simulations (neutronics, heat-transfer and heat pipe modeling) based on the MOOSE MultiApps system. In conclusion, the responses of the reactor to a series of transient scenarios were simulated to demonstrate the exceptional and inherent safety features of the novel microreactor concept.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Heat Exchangers Circuitry Optimization using Low-GWP Refrigerants in Reversible Heat Pump Applications

Tube-fin heat exchangers (TFHX) are widely used in heat pump applications. Circuitry optimization can improve system performance. Previous optimizations focus on improving component-level performance under a specific operating condition, i.e., the TFHX either works as a condenser or an evaporator. The optimal circuitry obtained under air conditioning (AC) mode cannot guarantee optimal performance when used in heat pump (HP) mode. This study implements a bi-objective formulation to achieve optimal system performance in both AC and HP modes. An integer permutation-based Genetic Algorithm is integrated with Heat Pump Design Model (HPDM) to perform heat pump optimization. Six refrigerants, i.e., R410A, R452B, R454B, R32, D2Y60 and L41a are investigated. Case studies show that optimal heat exchangers yield 2.1%-6.1% EER improvement under AC mode and 1.9%-8.5% COP improvement under HP mode. Use of this design approach can help assure a preferable performance of reversible heat pumps during both cooling and heating mode usage.

Li, Zhenning↗

Performance of an optimized rotor blade at off-design flight conditions

An investigation is made of the dynamic and aerodynamic performance of a helicopter rotor previously optimized for minimum 4/rev vertical shear and blade weight subject to certain dynamic and structural constraints. The program CAMRAD which was used in designing the optimized blade is used for both dynamic and aerodynamic analysis. The behavior of the optimized rotor is analyzed over a wide range of operating conditions and for a larger number rotor characteristics than those considered in designing the blade. To assess the dynamic behavior, the blade root vibratory shears and moments that are transmitted to the rotor hub are calculated. The aerodynamic performance assessments are made based on the power required by the rotor for a given rotor task, the rotor lifting efficiencies, maximum rotor thrust envelopes and the control margins. Results are presented for the optimized blade and the reference blade which was used as the baseline for the optimized blade, for two rotor tasks.

Chattopadhyay, Aditi↗

Performance of an optimized rotor blade at off-design flight conditions

An investigation is made of the dynamic and aerodynamic performance of a helicopter rotor previously optimized for minimum 4/rev vertical shear and blade weight subject to certain dynamic and structural constraints. The program CAMRAD which was used in designing the optimized blade is used for both dynamic and aerodynamic analaysis. The behavior of the optimized rotor is analyzed over a wide range of operating conditions and for a larger number of rotor characteristics than those considered in designing the blade. To assess the dynamic behavior, the blade root vibratory shears and moments that are transmitted to the rotor hub are calculated. The aerodynamic performance assessments are made based on the power required by the rotor for a given rotor task, the rotor lifting efficiencies, maximum rotor thrust envelopes and the control margins. Results are presented for the optimized blade and the control margins. Results are presented for the optimized blade and the reference blade, which was used as the baseline for the optimized blade, for two rotor tasks.

Chattopadhyay, Aditi↗

Geomancy: Automated Performance Enhancement through Data Layout Optimization

Large distributed storage systems such as high- performance computing (HPC) systems used by national or international laboratories require sufficient performance and scale for demanding scientific workloads and must handle shifting workloads with ease. Ideally, data is placed in locations to optimize performance, but the size and complexity of large storage systems inhibit rapid effective restructuring of data layouts to maintain performance as workloads shift. To address these issues, we have developed Geomancy, a tool that models the placement of data within a distributed storage system and reacts to drops in performance. Using a combination of machine learning techniques suitable for temporal modeling, Geomancy determines when and where a bottleneck may happen due to changing workloads and suggests changes in the layout that mitigate or prevent them. Our approach to optimizing throughput offers benefits for storage systems such as avoiding potential bottlenecks and increasing overall I/O throughput from 11% to 30%.

Bel, Oceane M.↗

Use of optimization to predict the effect of selected parameters on commuter aircraft performance

An optimizing computer program determined the turboprop aircraft with lowest direct operating cost for various sets of cruise speed and field length constraints. External variables included wing area, wing aspect ratio and engine sea level static horsepower; tail sizes, climb speed and cruise altitude were varied within the function evaluation program. Direct operating cost was minimized for a 150 n.mi typical mission. Generally, DOC increased with increasing speed and decreasing field length but not by a large amount. Ride roughness, however, increased considerably as speed became higher and field length became shorter.

Wells, V. L.↗

Performance Analysis of Optimized STARC-ABL Designs Across the Entire Mission Profile

Boundary layer ingestion (BLI) offers the potential for significant fuel burn reduction by exploiting strong aeropropulsive interactions. NASA’s STARC–ABL concept uses an electri- cally powered BLI tail cone thruster on what is otherwise a traditional airframe. Despite the traditional airframe of this configuration, aeropropulsive integration is critical to the perfor- mance of the BLI propulsor. Furthermore, due to being electrically powered, the fan pressure ratio and efficiency of the BLI tail cone thruster vary widely across the flight envelope, and this variation in fan performance must be accounted for with the aeropropulsive integration of the BLI system. Thus, accurate performance prediction for this novel propulsion configu- ration requires the use of a coupled aeropropulsive model across the flight envelope. In this work, we analyze the off-design performance of 18 optimized designs using an aeropropulsive model that is built with the OpenMDAO framework to couple 3-D RANS CFD simulations to 1-D thermodynamic cycle analyses. The designs are created via high-fidelity aeropropulsive design optimizations that span a range of fan pressure ratio and thrust values at the cruise conditions for the STARC-ABL concept, which was chosen as the aerodynamic design point for the propulsor. Performance analyses we present herein are then performed at a range of off-design flight conditions that span the flight envelope, including low-speed and low-altitude flight conditions. This study provides the first set of high-fidelity data for the STARC–ABL configuration at off-design conditions, and the results quantify the power savings through BLI compared to a traditional propulsion system across the entire mission profile.

optimization↗

Performance Analysis and Optimization on the UCLA Parallel Atmospheric General Circulation Model Code

An analysis is presented of several factors influencing the performance of a parallel implementation of the UCLA atmospheric general circulation model (AGCM) on massively parallel computer systems. Several modificaitons to the original parallel AGCM code aimed at improving its numerical efficiency, interprocessor communication cost, load-balance and issues affecting single-node code performance are discussed.

atmospheric study optimization strategies parallel↗

A Review Towards the Design Optimization of High Performance Additively Manufactured Rotating Detonation Rocket Engine Injectors

Rotating Detonation Rocket Engines (RDRE) have been marketed primarily for their higher specific impulse potential over constant pressure (CP) liquid rocket engines. However, several other performance advantages exist with RDREs over CP engines such as heat transfer advantages for gas expander cycle, increased completeness of combustion at low chamber L*, compact engine design, reduced coolant channel pressure drop potential, and improved injector C* performance. NASA has paved the way for liquid engine system performance enhancement since the Apollo program and continues to do so with metal additive manufacturing (AM), super-alloy materials, and advanced propulsion concepts. A team of propulsion development engineers at NASA are in the process of developing high-performance 7K lbf class RDRE hardware for their potential use in lander, upper stage, and even launch vehicle applications. Clear advantages have been demonstrated with AM including program cost and schedule reductions of up to 50%. It is well known that injector performance is integrally linked to the global performance of a combustion device. This is especially the case for RDREs since detonation stability is heavily dependent on the mixedness of propellants. A major program goal is to rapidly produce ultra-high-performance AM injectors. This paper reviews the available literature on liquid rocket injector design optimization as well as the experimental work conducted to date on injectors tested in RDREs. Major lessons learned are document and suggestions given towards the design of high-performance liquid RDRE injectors. In addition, the integration of metal AM into the design of liquid RDRE injector schemes is discussed. Finally, several candidate AM RDRE injector elements were produced to obtain their diodicity and cold flow characteristics.

rotating detonation engine↗

aphBO-2GP-3B: a budgeted asynchronous parallel multi-acquisition functions for constrained Bayesian optimization on high-performing computing architecture

High-fidelity complex engineering simulations are often predictive, but also computationally expensive and often require substantial computational efforts. The mitigation of computational burden is usually enabled through parallelism in high-performance cluster (HPC) architecture. Optimization problems associated with these applications is a challenging problem due to the high computational cost of the high-fidelity simulations. In this paper, an asynchronous parallel constrained Bayesian optimization method is proposed to efficiently solve the computationally expensive simulation-based optimization problems on the HPC platform, with a budgeted computational resource, where the maximum number of simulations is a constant. The advantage of this method are three-fold. Firstly, the efficiency of the Bayesian optimization is improved, where multiple input locations are evaluated parallel in an asynchronous manner to accelerate the optimization convergence with respect to physical runtime. This efficiency feature is further improved so that when each of the inputs is finished, another input is queried without waiting for the whole batch to complete. Second, the proposed method can handle both known and unknown constraints. Third, the proposed method samples several acquisition functions based on their rewards using a modified GP-Hedge scheme. The proposed framework is termed aphBO-2GP-3B, which means asynchronous parallel hedge Bayesian optimization with two Gaussian processes and three batches. The numerical performance of the proposed framework aphBO-2GP-3B is comprehensively benchmarked using 16 numerical examples, compared against other 6 parallel Bayesian optimization variants and 1 parallel Monte Carlo as a baseline, and demonstrated using two real-world high-fidelity expensive industrial applications. The first engineering application is based on finite element analysis (FEA) and the second one is based on computational fluid dynamics (CFD) simulations.

97 MATHEMATICS AND COMPUTING↗

Visual Analytics of Performance of Quantum Computing Systems and Circuit Optimization

Driven by potential exponential speedups in business, security, and scientific scenarios, interest in quantum computing is surging. This interest feeds the development of quantum computing hardware, but several challenges arise in optimizing application performance for hardware metrics (e.g., qubit coherence and gate fidelity). In this work, we describe a visual analytics approach for analyzing the performance properties of quantum devices and quantum circuit optimization. Our approach allows users to explore spatial and temporal patterns in quantum device performance data and it computes similarities and variances in key performance metrics. Detailed analysis of the error properties characterizing individual qubits is also supported. We also describe a method for visualizing the optimization of quantum circuits. The resulting visualization tool allows researchers to design more efficient quantum algorithms and applications by increasing the interpretability of quantum computations.

Chae, Junghoon↗