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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

RADAR: Runtime Asymmetric Data-access Driven Scientific Data Replication

Efficient I/O on large-scale spatiotemporal scientific data requires scrutiny of both the logical layout of the data (e.g., row-major vs. column-major) and the physical layout (e.g., distribution on parallel filesystems). For increasingly complex datasets, hand optimization is a difficult matter prone to error and not scalable to the increasing heterogeneity of analysis workloads. Given these factors, we present a partial data replication system called RADAR. We capture datatype- and collective-aware I/O access patterns (indicating logical access) via MPI-IO tracing and use a combination of coarse-grained and fine-grained performance modeling to evaluate and select optimized physical data distributions for the task at hand. Unlike conventional methods, we store all replica data and metadata, along with the original untouched data, under a single file container using the object abstraction in parallel filesystems. Our system results in manyfold improvements in some commonly used subvolume decomposition access patterns.Moreover, the modeling approach can determine whether such optimizations should be undertaken in the first place.

access pattern↗
DOE OSTI2020

Liquid-Cooled Heat Sink Optimization for Thermal Imbalance Mitigation in Wide-Bandgap Power Modules

Power semiconductor die layout in substrates used in power modules is generally optimized for minimum electrical parasitics (e.g., stray inductance) by considering the minimum spacing between dies for thermal decoupling. The layout assumes sufficient heat spreading and transfer from dies to the cooling structure. For module designs using a direct substrate cooling method, the base plate is removed, leading to a steady-state thermal asymmetry in the power module due to insufficient heat spreading/transfer. This causes significant temperature differences among the devices. Such unintentional thermal asymmetries can lead to undesirable asymmetries in power conversion among semiconductor devices, which impact reliability. This article proposes a thermal imbalance mitigation method that uses evolutionary optimized liquid-cooled heat sinks to improve the thermal loading among devices.

Sahu, Raj↗
DOE OSTI2018

NUMA-Aware Thread Scheduling for Big Data Transfers over Terabits Network Infrastructure

The evergrowing trend of big data has led scientists to share and transfer the simulation and analytical data across the geodistributed research and computing facilities. However, the existing data transfer frameworks used for data sharing lack the capability to adopt the attributes of the underlying parallel file systems (PFS). LADS (Layout-Aware Data Scheduling) is an end-to-end data transfer tool optimized for terabit network using a layout-aware data scheduling via PFS. However, it does not consider the NUMA (Nonuniform Memory Access) architecture. In this paper, we propose a NUMA-aware thread and resource scheduling for optimized data transfer in terabit network. First, we propose distributed RMA buffers to reduce memory controller contention in CPU sockets and then schedule the threads based on CPU socket and NUMA nodes inside CPU socket to reduce memory access latency. We design and implement the proposed resource and thread scheduling in the existing LADS framework. Experimental results showed from 21.7% to 44% improvement with memory-level optimizations in the LADS framework as compared to the baseline without any optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

High-performance strategies for the recent MRSF-TDDFT in GAMESS

Multiple ERI (Electron Repulsion Integral) tensor contractions (METC) with several matrices are ubiquitous in quantum chemistry. In response theories, the contraction operation, rather than ERI computations, can be the major bottleneck, as its computational demands are proportional to the multiplicatively combined contributions of the number of excited states and the kernel pre-factors. Here, this paper presents several high-performance strategies for METC. Optimal approaches involve either the data layout reformations of interim density and Fock matrices, the introduction of intermediate ERI quartet buffer, and loop-reordering optimization for a higher cache hit rate. The combined strategies remarkably improve the performance of the MRSF (mixed reference spin flip)-TDDFT (time-dependent density functional theory) by nearly 300%. The results of this study are not limited to the MRSF-TDDFT method and can be applied to other METC scenarios.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Communication Characterization and Optimization of Applications Using Topology-Aware Task Mapping on Large Supercomputers

On large supercomputers, the job scheduling systems may assign a non-contiguous node allocation for user applications depending on available resources. With parallel applications using MPI (Message Passing Interface), the default process ordering does not take into account the actual physical node layout available to the application. This contributes to non-locality in terms of physical network topology and impacts communication performance of the application. In order to mitigate such performance penalties, this work describes techniques to identify suitable task mapping that takes the layout of the allocated nodes as well as the application's communication behavior into account. During the first phase of this research, we instrumented and collected performance data to characterize communication behavior of critical US DOE (United States - Department of Energy) applications using an augmented version of the mpiP tool. Subsequently, we developed several reordering methods (spectral bisection, neighbor join tree etc.) to combine node layout and application communication data for optimized task placement. We developed a tool called mpiAproxy to facilitate detailed evaluation of the various reordering algorithms without requiring full application executions. This work presents a comprehensive performance evaluation (14,000 experiments) of the various task mapping techniques in lowering communication costs on Titan, the leadership class supercomputer at Oak Ridge National Laboratory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Communication Characterization and Optimization of Applications Using Topology-Aware Task Mapping on Large Supercomputers

On large supercomputers, the job scheduling systems may assign a non-contiguous node allocation for user applications depending on available resources. With parallel applications using MPI (Message Passing Interface), the default process ordering does not take into account the actual physical node layout available to the application. This contributes to non-locality in terms of physical network topology and impacts communication performance of the application. In order to mitigate such performance penalties, this work describes techniques to identify suitable task mapping that takes the layout of the allocated nodes as well as the application's communication behavior into account. During the first phase of this research, we instrumented and collected performance data to characterize communication behavior of critical US DOE (United States - Department of Energy) applications using an augmented version of the mpiP tool. Subsequently, we developed several reordering methods (spectral bisection, neighbor join tree etc.) to combine node layout and application communication data for optimized task placement. We developed a tool called mpiAproxy to facilitate detailed evaluation of the various reordering algorithms without requiring full application executions. This work presents a comprehensive performance evaluation (14,000 experiments) of the various task mapping techniques in lowering communication costs on Titan, the leadership class supercomputer at Oak Ridge National Laboratory.

Sreepathi, Sarat↗
DOE OSTI2017

Exploring performance and energy tradeoffs for irregular applications: A case study on the Tilera many-core architecture

High performance, parallel applications with irregular data accesses are becoming a critical workload class for modern systems. In particular, the execution of such workloads on emerging many-core systems is expected to be a significant component of applications in data mining, machine learning, scientific computing and graph analytics. However, power and energy constraints limit the capabilities of individual cores, memory hierarchy and on-chip interconnect of such systems, thus leading to architectural and software trade-os that must be understood in the context of the intended application’s behavior. Irregular applications are notoriously hard to optimize given their data-dependent access patterns, lack of structured locality and complex data structures and code patterns. We have ported two irregular applications, graph community detection using the Louvain method (Grappolo) and high-performance conjugate gradient (HPCCG), to the Tilera many-core system and have conducted a detailed study of platform-independent and platform-specific optimizations that improve their performance as well as reduce their overall energy consumption. To conduct this study, we employ an auto-tuning based approach that explores the optimization design space along three dimensions - memory layout schemes, GCC compiler flag choices and OpenMP loop scheduling options. We leverage MIT’s OpenTuner auto-tuning framework to explore and recommend energy optimal choices for different combinations of parameters. We then conduct an in-depth architectural characterization to understand the memory behavior of the selected workloads. Finally, we perform a correlation study to demonstrate the interplay between the hardware behavior and application characteristics. Using auto-tuning, we demonstrate whole-node energy savings and performance improvements of up to 49:6% and 60% relative to a baseline instantiation, and up to 31% and 45:4% relative to manually optimized variants.

auto tuning↗
DOE OSTI2019

Design and Characterization of High Thermal Conductivity Pipes from Roll-to- Roll Processed Hybrid Copper-Polymer Strips for Waste Heat Recovery

Metal based heat exchangers targeting low temperature (<150°C) waste heat recovery (WHR) face high maintenance and material costs [1] that result in long payback periods (>1 year). Low-cost polymer pipes suffer from poor thermal conductivity (~0.2 W/m.K), and thus a low overall heat transfer coefficient. Previous reports demonstrated thermal conductivity enhancement in polymers through systematic molecular alignment [2, 3, 4], or by metal micro-particle inclusions [5]. However, these approaches suffer from scalability issues for WHR heat exchangers in terms of cost [1, 3], and thermomechanical considerations [6, 7]. In this work, we propose hybrid metal-polymer strips that are strategically designed to enhance thermal conductivity by cladding copper around polymer strips. The polymer strips with copper-clad edges are wound helically to form the pipes for a heat exchanger. Through numerical simulations, we optimize the copper-polymer strip layouts to achieve high wall thermal conductivity (k > 1 W/m.K) and also have low volume fraction of copper (<70%) for the composite pipes. In copper-polymer composite heat exchangers, the bottlenecks for heat transfer are the thermal interfacial resistances of copper-copper and copper-polymer joints. We experimentally measured interfacial resistances to be ~1x10 -5 K.m 2 /W and ~4x10 -5 K.m 2 /W for copper-copper and copper-polymer joints, respectively. Using the measured interfacial resistances, we further optimized the design of the hybrid pipes to find high thermal conductivity (> 1 W/m.K) designs. We predict up to ~20 % enhancement in overall heat transfer relative to an all polymer (k = 0.2 W/m.K) heat exchanger system. Using a cohesive zone modelling (CZM) for predicting delamination at the weld joints, we find that our hybrid pipes can have operating internal pressures > 200 psi. The optimized designs of hybrid metal-polymer pipes provide a scalable and cost- effective means for harvesting waste heat from low temperature sources. Thekdi, A., and Nimbalkar, S. Oak Ridge National Lab (2014). Shen, Sheng, et al. Nature nanotechnology 5.4 (2010). Xu, Yanfei, et al. Science advances 4.3 (2018). Smith et al. ACS nano, 9(2), (2015). Sofian, N.M., et al., Journal of Thermoplastic Composite Materials (2001). Aymonier et al. Chemistry of Materials, 15(25), (2003). Tavman, I.H., Journal of Applied Polymer Science, 62(12), (1996).

C Rajagopal, Manjunath↗
DOE OSTI2025

Web-Based Tools for Data-Informed Remedy Optimization: Software Theory and User Guide

This report documents the development and application of two web-based decision-support tools for pump-and-treat (P&T) groundwater remediation systems: PTOLEMY (Pump-and-Treat Optimized Location Evaluation to Maximize Yields) and OPTIMA (Optimization for Pump-and-Treat Implementation, Management, & Assessment). These tools enhance remedy design and management by leveraging advanced computational methods – specifically deep learning and multi-objective optimization – within a user-friendly platform. By integrating data-driven models with established hydrogeological knowledge, PTOLEMY and OPTIMA enable more efficient evaluation of well placement and operational strategies, helping site managers balance multiple remediation objectives under complex conditions. Both tools are implemented as modules within the SOCRATES (Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites) web platform, which provides data access, visualization, and analytics to support remedy optimization across sites in the U.S. Department of Energy Office of Environmental Management complex. PTOLEMY is a rapid screening module designed to identify promising locations for new extraction wells. It employs a multi-channel three-dimensional convolutional neural network (MC3D-CNN) trained on high-fidelity simulation data to predict the relative performance (in terms of contaminant mass recovery) of potential well sites. Through an interactive web interface, PTOLEMY visualizes the probability of high performance across a site, highlighting areas where an extraction well is likely to yield above-threshold contaminant removal over a multi-year period. PTOLEMY’s map-based displays and exportable results support transparent communication of screening analyses. By focusing attention on the most favorable candidate locations, the tool augments traditional engineering judgment and physics-based modeling, providing a data informed basis for subsequent detailed evaluations. OPTIMA is a multi objective optimization module designed to find wellfield layouts and operating schedules that meet various cleanup goals. It quickly evaluates thousands of candidate setups – combinations of well locations, timing, and rates – and returns a small set of best trade-off options for comparison. At its core, OPTIMA uses a U-Net-based surrogate model – a deep-learning emulator of a groundwater flow and transport simulator – to dramatically accelerate scenario evaluations. Coupling this fast surrogate with the NSGA-II (Non-dominated Sorting Genetic Algorithm II) evolutionary algorithm, OPTIMA explores a wide decision space of well locations and schedules to identify Pareto-optimal solutions that trade off key objectives (e.g., minimizing cleanup time, maximizing contaminant mass removal, and minimizing plume extent). The tool outputs a family of optimal configurations and visualizes their trade-offs (Pareto frontiers of cleanup metrics and maps of optimized well placements). Site managers can use these results to understand the range of viable strategies and to select candidate designs for more detailed verification. OPTIMA is currently under active development and not yet fully released; this guide provides early documentation to support planning and gather user feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

NAMSA

In NAMSA, we introduce two main solutions to address the limitations of MSA-type algorithms for simulation of electron scattering/microscopy data: just-in-time compilation and work partitioning via MPI and GPU-to-GPU communication. First, the just-in-time (JIT) compilation strategy produces optimally tuned CUDA C++ kernels due to the data layout being perfectly known at runtime and compiled via calls from the Python interpreter. NAMSA automatically optimizes the 2-D FFT planning, and CUDA multi-streams scheduling/launching of probe simulations. With NAMSA, we can simulate electron scattering/microscopy on hundreds to thousands of GPUs, while removing the major limitations of memory and bandwidth from MSA.

Laanait, Nouamane↗
DOE OSTI2022

Front-End Engineering Design for Piperazine with the Advanced Stripper

This Department of Energy (DOE) funded project was executed with the goal of preparing a Front-End Engineering Design (FEED) for the capture and compression of 90% of the CO2 that would normally be emitted from an existing natural gas combined cycle (NGCC) plant. The FEED focused on the application of the piperazine advanced stripper (PZAS) process at Mustang Station of the Golden Spread Electric Cooperative (GSEC), which consists of two gas turbines with common heat recovery steam generator (HRSG). The University of Texas at Austin (UT) served as the prime contractor, and subcontracted AECOM Technical Services and Trimeric Corporation to support FEED development. This project team has worked together to advance PZAS for more than a decade. ExxonMobil, Chevron, and Total provided project co-funding. The objectives of this work included: 1. To advance engineering design such that a comprehensive estimate for the total installed cost of a full-scale PZAS CO2 Capture Plant with CO2 compression can be developed on an existing NGCC power plant. a. These detailed costs can also be used to qualify PZAS and other related second generation (2G) amine scrubbing processes for use on cogeneration facilities in refineries and chemical plants that use gas turbines with HRSGs to produce steam. b. These detailed costs will help qualify 2G amine scrubbing for use on NGCC power plants and establish a more accurate baseline cost to be used as a target by other capture technologies. 2. To provide cost details to be used in the economic optimization of the process features of PZAS and other 2G amine scrubbing processes. 3. To provide DOE with a more detailed understanding of carbon capture costs in a commercial application, enabling DOE to better design its R&D program to improve the economics for carbon capture. 4. To provide the host site and cost share partners with the information necessary to determine whether a commercial project to capture and use CO2 for enhanced oil recovery (EOR) or for sequestration can be justified (when accounting for the 45Q tax credit). A key component of the FEED is the estimated total installed cost, which provides a basis for the likely capital investment necessary to implement the PZAS carbon capture process at this location and scale. In combination with the included economic analysis, which accounts for potential revenue from the produced CO2, potential avenues to profitability are explored. The major findings of the FEED are as follows: The Mustang Station PZAS CO2 Capture Plant estimated total project cost of $698 MM of which $384 MM was direct costs. The annual operating costs were $32.6 MM. The total investment for a PZAS facility at Mustang Station is $725 MM. This estimate includes owner’s cost of $25 million and a contingency of $110 MM. • The study estimated the CO2 capture plant at Mustang Station would generate CO2 at $110/tonne for EOR, assuming a 12% IRR (internal rate of return) and an 85% capacity factor. For CO2 storage, the same case would achieve a 12% IRR at about $114/tonne. At a capacity factor of 52%, the storage and EOR cases would break even when carbon is priced ~$150/tonne. The economic analysis determined that the capacity factor and utility pricing, among other variable factors, had a significant effect on the economics and will need additional studied. • The energy penalty of the PZAS plant would be about 46 MW in connected power and 35 MW in operating load. The natural gas requirement (for the Gas Boiler package) would be about 354 MMBTU/hr. • The FEED revealed no major risks in process maturity. However, some areas were outlined for further engineering during detailed design, which included the Gas Boiler system, general arrangement and site layout, air coolers, schedule development, and optimization of the process for higher CO2 removal. • If PZAS were to be implemented at another host site, additional opportunities for cost reduction for would include cost reduction through use of cooling water and steam extraction.

03 NATURAL GAS↗
DOE OSTI2019

FTLADS: Object-Logging Based Fault-Tolerant Big Data Transfer System Using Layout Aware Data Scheduling

The layout-aware data scheduling (LADS) data movement framework optimizes congestion for end-to-end data transfers. During data transfer, LADS can avoid congested storage elements by exploiting the underlying storage layout at each endpoint. This improves the I/O bandwidth and hence the data transfer rate across high-speed networks. However, the absence of fault tolerance (FT) in LADS results in data retransmission overhead and may lead to possible data integrity issues upon faults. In this paper, we propose object-logging FT mechanisms to avoid transmitting the objects that are successfully written into the parallel file system (PFS) at the sink end. Depending on the number of log files created for the whole dataset, we have classified our FT mechanisms into three different categories: file logger, transaction logger, and universal logger. Also, to address the space overhead, we have proposed different methods of populating the log files with the information of the successfully transferred objects. We have evaluated the data transfer performance and recovery time overhead of the proposed object-logging-based FT mechanisms on the LADS data transfer framework. Our experimental results reflect that FT mechanisms exhibit negligible overhead (<; 1%) with respect to the data transfer time. Yet, the fault recovery time is 10% higher than the total data transfer time at any fault point.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Minimizing total energy cost and tardiness penalty for a scheduling-layout problem in a flexible job shop system: A comparison of four metaheuristic algorithms

Job scheduling and machine layout are interrelated in improving energy consumption (EC) and productivity measures such as tardiness and represent two important decisions that must be made by manufacturers. This interdependency can be explained by transportation time, which connects scheduling and layout. Scheduling and layout, however, have not been thoroughly studied in conjunction using an integrated model in the context of sustainable manufacturing. Hence, we propose an energy-aware optimization model in which scheduling is integrated with layout in a single-level framework. More specifically, a single objective function is defined to minimize the facility energy cost and the job tardiness penalty, which control EC and tardiness respectively in a flexible job shop system. In order to model machine EC more accurately, we also consider three different machine states: a processing state and two idle states. Our case studies show that the integrated model exhibits better performance in controlling manufacturing EC and job tardiness than a non-integrated model in which machine locations are uncontrollable and transportation times between machines are unchangeable. To deal with large-sized problems, we also introduce four new metaheuristics. The performances of these new metaheuristics are compared in terms of objective function values and CPU times using various case studies. The results indicate that a hybrid ant colony optimization and simulated annealing (ACO-SA) algorithm provides better performance than the other algorithms. Specifically, our case studies show that the integrated model using ACO-SA can improve the objective function value by around 5% when compared to the non-integrated model.

42 ENGINEERING↗
DOE OSTI2025

Characterizing in-stream turbulent flow for tidal energy converter siting in Cook Inlet, Alaska

Cook Inlet in Alaska is the most promising location for tidal energy development in the U.S. due to its significant tidal range of approximately 10 meters and high volume flux. The inlet's unique geometry and flow characteristics make it the most energetic tidal stream in the nation, with GW-scale potential energy capacity. With the growing interest in tidal energy converter (TEC) deployment in this area, we implemented a regional-scale, 3D hydrodynamic modeling framework to predict tidal current and turbulence characteristics that can assist TEC designers and project managers. We validated the model results extensively using various datasets collected with bottom-mounted acoustic Doppler current profilers and velocimeters. The comparison between the model outputs and observational data highlighted the effectiveness of the 3D FVCOM model and the Mellor-Yamada Level 2.5 Turbulence Model in accurately assessing macro-scale kinetic energy, turbulence intensity, and the production and dissipation rates at a prospective TEC site. Using two months of model simulation data, we examined the channel cross-section for TEC deployment, focusing on undisturbed power density and macro-scale turbulent properties. Further, our findings indicate that understanding the turbulence characteristics and flow properties can enhance Stage I/II resource characterization by identifying optimal locations for TECs and their layouts within the channel. Furthermore, we demonstrated that TEC designers can utilize macro-scale turbulence data from 3D coastal models as boundary conditions for other turbulence models, allowing for a more detailed resolution of the turbulence structure at TEC siting locations. Ultimately, this work emphasizes the importance of estimating flow and turbulence conditions in energetic systems to understand turbulent sites better and improve resource characterization.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Thermal Optimization of a Silicon Carbide, Half-Bridge Power Module

This project describes the modeling process to design the packaging and heat exchanger for a half-bridge wide-bandgap (WBG) power semiconductor module. The module uses two silicon carbide, metal-oxide-semiconductor field-effect transistor (MOSFET) devices per switch position that are soldered to an aluminum nitride, direct-bond copper (DBC) substrate. A baseplate cooling configuration (e.g., no thermal grease) is used along with a water-ethylene glycol, jet-impingement-style heat exchanger. The heat exchanger was designed to be fabricated using prototyping equipment from the National Renewable Energy Laboratory, complies with automotive standards (for minimal channel sizes, flow rates, and coolant), and considers reliability aspects (i.e., erosion/corrosion). Device-scale computational fluid dynamics (CFD) is used first to design the slot jet impingement cooling configuration and compute the effective heat transfer coefficient (HTC) of the concept. The computed HTCs are then used as boundary conditions for a finite element study to optimize the package geometry (e.g., device layout and baseplate thickness) to minimize thermal resistance and minimize temperature variation between the module's four devices. Finally, a fluid manifold is designed to generate the slot jets and cool the devices. Module-scale CFD predicts a relatively low junction-to-fluid thermal resistance of 16.7 mm2 K/W, a 1.4 degrees C temperature variation between devices, and a total pressure drop of 5,860 Pa (0.85 psi) for the design. The thermal resistance of the module design is about 67% lower than the 2015 BMW i3 power electronics/modules thermal resistance.

DIRECT ENERGY CONVERSION↗
DOE OSTI2019

Multi-scale topology optimization of multi-material structures with controllable geometric complexity — Applications to heat transfer problems

This study presents a topology optimization method to design assemblies of periodic cellular materials with controllable geometric complexity. The framework is based on a novel multi-scale and multi-material design model in which the structure, the layout of the material subdomains, and their micro-structures are optimized concurrently. To allow a tight control over its geometrical complexity, the layout at the macro-scale is described by level-set fields, parameterized by geometric primitives. The micro-scale geometry is represented through a density approach. A nonlinear programming algorithm drives the optimization process using design sensitivities computed by the discrete adjoint method. The proposed design framework is studied with heat transfer problems. Practical design problems, such as a heat sink and a thermal storage unit with phase change are discussed. The macro-scale analysis model relies on a generalized transient diffusion equation. At the micro-scale, homogenization is used to compute equivalent material properties. The numerical examples in this study show that the optimized multi-scale multi-material layouts outperform the corresponding mono-scale structures while maintaining geometric simplicity at the macro-scale level.

42 ENGINEERING↗
DOE OSTI2020

Optimal Heliostat Assignment Strategy for Multiple-Receiver Systems

Next-generation concentrating solar power concepts currently being developed under the U.S. Department of Energy's Gen3 program include several novel heliostat field and receiver arrangements. Among these concepts are solar fields utilizing multiple receivers or several distinct receiver flux control zones, and each of which has particular power or peak flux constraints. In this paper, we present a linear program that identifies optimal heliostat-to-receiver assignment strategies for multi-receiver or multi-zone solar fields based on detailed calculations made by an optics modeling package. Two distinct problems are addressed: namely, (1) a design problem that chooses the optimal set of heliostats to include in a final layout given receiver constraints and performance, and (2) an operations problem that assigns existing heliostats to a receiver, maximizing field power output while maintaining receiver power constraints. The optimization methodology is integrated into the concentrating solar power tower modeling package SolarPILOTTM, and results are presented showing that heliostat assignment strategies can impact both initial heliostat field layout characteristics and the cost of thermal energy produced by the field. The methodology succeeds in maintaining power requirements but at the expense of producing different flux profiles on each receiver surface. Consequently, the paper also discusses additional measures that are applied to ensure that desirable flux distribution properties are maintained, reducing local flux mean-absolute-deviation values from a baseline of 17% or greater to less than 5% compared to a desired reference flux profile.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2019

Maximization of performance in multi-tube latent heat storage – Optimization of fins topology, effect of materials selection and flow arrangements

This paper addresses the need of multi-tube latent heat thermal storage (LHTES) systems with enhanced heat transfer performance. Uniquely, this work draws from topology optimization method for thermal energy storage to search for the optimal configuration of fins in multi-tube LHTES systems with different phase change materials (PCMs), flow arrangements and design constraints. The design freedom of topology optimization allows the discovery of innovative LHTES designs and elucidate the link between design and physical processes occurring during charging/discharging. Three key results of this study are: i) the optimized fin design is tightly connected to the type of storage duty cycle, which demonstrates the necessity to account for realistic operating conditions in the optimization process. ii) The fin material should be chosen in parallel with the layout of the fins and not sequentially as commonly done; this indicates that the optimization of LHTES systems is a co-design challenge. iii) Topology optimized multi-tube LHTES units surpass in performance fins optimized for a single-tube configuration in a multi-tube unit. Finally, this work demonstrates for the first time the manufacturability of topology-optimized LHTES units by using 3D printing.

25 ENERGY STORAGE↗