Search NASA⌕ Search

SEARCH · Search NASA

Results for “program optimizations”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,441 records · Page 80

PRO-X Fuel Cycle Transportation and Crosscutting Progress Report

The PRO-X program is actively supporting the design of nuclear systems by developing a framework to both optimize the fuel cycle infrastructure for advanced reactors (ARs) and minimize the potential for production of weapons-usable nuclear material. Three study topics are currently being investigated by Sandia National Laboratories (SNL) with support from Argonne National Laboratories (ANL). This multi-lab collaboration is focused on three study topics which may offer proliferation resistance opportunities or advantages in the nuclear fuel cycle. These topics are: 1) Transportation Global Landscape, 2) Transportation Avoidability, and 3) Parallel Modular Systems vs Single Large System (Crosscutting Activity).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Technology Development for ≥ 22.5% Efficient p-PERC Solar Cells

The overall objective of this program is to achieve ≥ 22.5 % bifacial p-type cell efficiencies by developing and implementing optimized homogeneous phosphorus (P) emitter on the front and tunnel oxide passivated boron (B) doped poly-Si contact (p-TOPCon) on the rear side, in combination with advanced fine-line screen-printing metallization and high bulk lifetime in the base material.

14 SOLAR ENERGY↗

Ion-Pair Proton Exchange Membrane Fuel Cells for Heavy-duty Transportation

The purpose of this project is to build a fuel cell prototype that demonstrates high temperature proton exchange membrane fuel cell technology (HT PEMFC) commercial readiness. It advances from a technology baseline established in a prior CRADA in which these same Parties collaborated during the years 2020-2024. These efforts are aligned with the intentions of the DOE Hydrogen Fuel Cell Technology Office (HFTO) L’Innovator Pilot Program. Participant observes that its US-based competitive advantage may be improved by further optimizing Laboratory inventions. This CRADA is intended to further improve National Laboratory compositions and to develop commercial HT PEMFC membrane electrode assemblies (MEAs) that perform over a range of operating temperatures and relative humidity, that generate power from both low grade and pure hydrogen, and that are resistant to air impurities. Participant’s goal is to advance the commercial competitiveness of National Laboratory technologies in fuel cell products for heavy-duty truck integrators, for stationary power generation, marine applications, and for emerging interest from commercial aviation. The Parties will collaborate on producing a HT PEMFC MEA that integrates LANL ion pair technology and Brookhaven catalyst technology. The Laboratories plan to research and develop compositions for testing and evaluation. The participant will manufacture multiple MEAs based on the Laboratory compositions and will enable selected customers to validate performance characteristics. The Laboratories will convey to Participant the methods of making the National Laboratory compositions such that Participant may reproduce and then scale Laboratory methods into commercial production. Throughout the project, the Laboratories and Participant will iteratively test and optimize the compositions of materials of the MEAs, intending to optimize characteristics such as power density and lifecycle durability. Participant’s intended customers include fuel cells for large trucks, aviation, power back up, marine, and portable power.

99 GENERAL AND MISCELLANEOUS↗

An Evaluation of the Economic and Resilience Benefits of a Microgrid in Northampton, Massachusetts

Recent developments and advances in distributed energy resource (DER) technologies make them valuable assets in microgrids. This paper presents an innovative evaluation framework for microgrid assets to capture economic benefits from various grid and behind-the-meter services in grid-connecting mode and resilience benefits in islanding mode. In particular, a linear programming formulation is used to model different services and DER operational constraints to determine the optimal DER dispatch to maximize economic benefits. For the resiliency analysis, a stochastic evaluation procedure is proposed to explicitly quantify the microgrid survivability against a random outage, considering uncertainties associated with photovoltaic (PV) generation, system load, and distributed generator failures. Optimal coordination strategies are developed to minimize unserved energy and improve system survivability, considering different levels of system connectedness. The proposed framework has been applied to evaluate a proposed microgrid in Northampton, Massachusetts that would link the Northampton Department of Public Works, Cooley Dickenson Hospital, and Smith Vocational Area High School. The findings of this analysis indicate that over a 20-year economic life, a 441 kW/441 kWh battery energy storage system, and 386 kW PV solar array can generate $2.5 million in present value benefits, yielding a 1.16 return on investment ratio. Results of this study also show that forming a microgrid generally improves system survivability, but the resilience performance of individual facilities varies depending on power-sharing strategies.

25 ENERGY STORAGE↗

Flexible Coal: An Example Evolution from Baseload to Peaking Plant (Presentation)

Twenty-first century power systems, with higher penetration levels of low-carbon energy, smart grids, and other emerging technologies, will favor resources that have low marginal costs and provide system flexibility (e.g., the ability to cycle on and off to follow changes in variable renewable energy plant output). Questions remain about both the fate of coal plants in this scenario and whether they can cost-effectively continue to operate if they cycle routinely. The experience from the CGS plant demonstrates that coal plants can become flexible resources. This flexibility - namely the ability to cycle on and off and run at lower output (below 40% of capacity) - requires limited hardware modifications but extensive modifications to operational practice. Cycling does damage the plant and impact its life expectancy compared to baseload operations. Nevertheless, strategic modifications, proactive inspections and training programs, among other operational changes to accommodate cycling, can minimize the extent of damage and optimize the cost of maintenance. CGS's cycling, but not necessarily the associated price tag, is replicable. Context - namely, power market opportunities and composition of the generation fleet - will help determine for other coal plants the optimal balance between the level of cycling-related forced outages and the level of capital investment required to minimize those outages. Replicating CGS's experience elsewhere will likely require a higher acceptance of forced outages than regulators and plant operators are accustomed to; however, an increase in strategic maintenance can minimize the impact on outage rates.

01 COAL, LIGNITE, AND PEAT↗

Flexible Coal: An Example Evolution from Baseload to Peaking Plant (Presentation)

Twenty-first century power systems, with higher penetration levels of low-carbon energy, smart grids, and other emerging technologies, will favor resources that have low marginal costs and provide system flexibility (e.g., the ability to cycle on and off to follow changes in variable renewable energy plant output). Questions remain about both the fate of coal plants in this scenario and whether they can cost-effectively continue to operate if they cycle routinely. The experience from the CGS plant demonstrates that coal plants can become flexible resources. This flexibility - namely the ability to cycle on and off and run at lower output (below 40% of capacity) - requires limited hardware modifications but extensive modifications to operational practice. Cycling does damage the plant and impact its life expectancy compared to baseload operations. Nevertheless, strategic modifications, proactive inspections and training programs, among other operational changes to accommodate cycling, can minimize the extent of damage and optimize the cost of maintenance. CGS's cycling, but not necessarily the associated price tag, is replicable. Context - namely, power market opportunities and composition of the generation fleet - will help determine for other coal plants the optimal balance between the level of cycling-related forced outages and the level of capital investment required to minimize those outages. Replicating CGS's experience elsewhere will likely require a higher acceptance of forced outages than regulators and plant operators are accustomed to; however, an increase in strategic maintenance can minimize the impact on outage rates.

01 COAL, LIGNITE, AND PEAT↗

Flexible Computer Science Infrastructure (FleCSI)

FleCSI is a compile-time configurable framework designed to support multi-physics application development. As such, FleCSI attempts to provide a very general set of infrastructure design patterns that can be specialized and extended to suit the needs of a broad variety of solver and data requirements. Current support includes multi-dimensional mesh topology, mesh geometry, and mesh adjacency information, n-dimensional hashed-tree data structures, graph partitioning interfaces, and dependency closures. FleCSI also introduces a functional programming model with control, execution, and data abstractions that are consistent with both MPI and state-of-the-art task-based runtimes such as Legion and Charm++. The FleCSI abstraction layer provides the developer with insulation from the underlying runtime, while allowing support for multiple runtime systems, including conventional models like asynchronous MPI. The intent is to give developers a concrete set of user-friendly programming tools that can be used now, while allowing flexibility in choosing runtime implementations and optimizations that can be applied to architectures and runtimes that arise in the future. The control and execution models in FleCSI also provide formal nomenclature for describing poorly understood concepts like kernels and tasks.

Bergen, Ben↗

Design Considerations for Proposed Fermilab Integrable RCS

Integrable optics is an innovation in particle accelerator design that provides strong nonlinear focusing while avoiding parametric resonances. One promising application of integrable optics is to overcome the traditional limits on accelerator intensity imposed by betatron tune-spread and collective instabilities. The efficacy of high-intensity integrable accelerators will be undergo comprehensive testing over the next several years at the Fermilab Integrable Optics Test Accelerator (IOTA) and the University of Maryland Electron Ring (UMER). We propose an integrable Rapid-Cycling Synchrotron (iRCS) as a replacement for the Fermilab Booster to achieve multi-MW beam power for the Fermilab high-energy neutrino program. We provide a overview of the machine parameters and discuss an approach to lattice optimization. Integrable optics requires arcs with integer-pi phase advance followed by drifts with matched beta functions. We provide an example integrable lattice with features of a modern RCS - long dispersion-free drifts, low momentum compaction, superperiodicity, chromaticity correction, separate-function magnets, and bounded beta functions.

43 PARTICLE ACCELERATORS↗

Linear optimal power flow system and method

An electric power system or power grid is optimized using a computer-implemented tool the represents in computer memory the optimization function and at least one constraint, which the processor operates upon using a linear programming solver algorithm. The constraints are represented in memory as data structures that include both real and reactive power terms, corresponding to at least one of a power flow model and a transmission line model. The transmission line model is represented using a piecewise linear representation. The power flow model may also include for each node in the power system a real power loss term representing transmission line loss allocated to that node.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Solving equilibrium problems using extended mathematical programming

We introduce an extended mathematical programming framework for specifying equilibrium problems and their variational representations, such as generalized Nash equilibrium, multiple optimization problems with equilibrium constraints, and (quasi-) variational inequalities, and computing solutions of them from modeling languages. We define a new set of constructs with which users annotate variables and equations of the model to describe equilibrium and variational problems. Our constructs enable a natural translation of the model from one formulation to another more computationally tractable form without requiring the modeler to supply derivatives. In the context of many independent agents in the equilibrium, we facilitate expression of sophisticated structures such as shared constraints and additional constraints on their solutions. We define shared variables and demonstrate their uses for sparse reformulation, economic equilibrium problems sharing economic states, mixed pricing behavior of agents, and so on. We give some equilibrium and variational examples from the literature and describe how to formulate them using our framework. Experimental results comparing performance of various complementarity formulations for shared variables are provided. Our framework has been implemented and is available within GAMS/EMP.

Equilibrium programming↗

Sparse Deep Neural Network Inference using different Programming Models

Sparse deep neural networks have gained increasing attention recently in achieving speedups on inference with reduced memory footprints. However, the real-world applications are little shown with specialized optimizations, yet a wide variety of DNN tasks remain dense without exploiting the advantages of sparsity in networks. Recent work presented by MIT/IEEE/Amazon GraphChallenge has demonstrated significant speedups and various techniques. Still, we find that there is limited investigation of the impact of various Python and C\slash C++ based programming models to explore new opportunities in general cases. In this work, we provide performance evaluation through different programming models using CuPy, cuSPARSE, and OpenMP to discuss the advantages and disadvantages of our sparse implementations on single-GPU and multiple GPUs of NVIDIA DGX-A100 40GB/80GB platforms.

machine learning, HPC↗

Achieving designed texture and flows in bulk active nematics using optimal control theory

Being intrinsically nonequilibrium, active materials can potentially perform functions that would be thermodynamically forbidden in passive materials. However, active systems have diverse local attractors that correspond to distinct dynamical states, many of which exhibit chaotic turbulent-like dynamics and thus cannot perform work or useful functions. Designing such a system to choose a specific dynamical state is a formidable challenge. Motivated by recent advances enabling optogenetic control of experimental active materials, we describe an optimal control theory framework that identifies a spatiotemporal sequence of light-generated activity that drives an active nematic system toward a prescribed dynamical steady state. Active nematics are unstable to spontaneous defect proliferation and chaotic streaming dynamics in the absence of control. We demonstrate that optimal control theory can compute activity fields that redirect the dynamics into a variety of alternative dynamical programs and functions. This includes dynamically reconfiguring between states, selecting and stabilizing emergent behaviors that do not correspond to attractors, and are hence unstable in the uncontrolled system. Furthermore, our results provide a roadmap to leverage optical control methods to rationally design structure, dynamics, and function in a wide variety of active materials.

Complex systems theory↗

LIBS Measurement in Vitrification of HLW Process: Towards a Development of Online Chemical Analyses - 18290

Research programs are currently underway in the Joint CEA-AREVA Vitrification Laboratory (LCV) to develop and optimize Laser Induced Breakdown Spectroscopy (LIBS) for nuclear waste streams analyses. The laboratory has full scale prototypes with the advantage of working on simulated inactive solutions of fission products. LIBS is an elemental chemical analysis technology that uses a short laser pulse to create a micro-plasma on the sample surface. This analytical technique offers many advantages compared to other techniques. It includes a sample preparation-free measurement and an extremely fast measurement time, from a few seconds to a few minutes. This paper presents the LIBS technique available in the laboratory. The first LIBS analyzes results of liquid samples from the off-gas treatment unit integrated on the full scale vitrification process are also presented and discussed. These complex solutions contain suspended particles and up to 30 chemical elements. A vision of an online LIBS analysis cell is also proposed with the development and associated research steps. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Formulations and Valid Inequalities for Optimal Black Start Allocation in Power Systems

The restoration of a power system after a blackout starts around units with enhanced technical capabilities, referred to as black start units (BSUs). We examine the planning problem of optimally allocating these units on the grid subject to a budget constraint. We present a mixed integer programming model based on current literature in power systems. Binary variables are associated with the allocation of BSUs and with the energization state of buses, branches, and generators of the power system over a time horizon. We extract a substructure of the feasible region which imposes the requirement that each island that appears during the restoration process must have at least one operational generator. We discuss three equivalent reformulations for this requirement. We introduce a family of exponentially many, polynomially separable, valid inequalities to strengthen the formulation. Under simplifying assumptions, we show that the convex hull of the feasible region is a full-dimensional polyhedron, and prove that some of the constraints we introduced are facet-defining. We perform experiments to examine the difference in strength between the formulations as well as the computational times to solve the problem to near optimality for synthetic instances of the IEEE-39, IEEE-118, Illinois-200, WECC-225, IEEE-300, South Carolina-500, and Texas-2000 power systems. We illustrate a use case of the model. We conclude by suggesting extensions of the current work for future research.

Black Start Allocation↗

A local-view array library for partitioned global address space C++programs

Multidimensional arrays are an important data structure in many scientific applications. Unfortunately, built-in support for such arrays is inadequate in C++, particularly in the distributed setting where bulk communication operations are required for good performance. In this paper, we present a multidimensional library for partitioned global address space (PGAS) programs, supporting the one-sided remote access and bulk operations of the PGAS model. The library is based on Titanium arrays, which have proven to provide good productivity and performance. These arrays provide a local view of data, where each rank constructs its own portion of a global data structure, matching the local view of execution common to PGAS programs and providing maximum flexibility in structuring global data. Unlike Titanium, which has its own compiler with array-specific analyses, optimizations, and code generation, we implement multidimensional arrays solely through a C++library. The main goal of this effort is to provide a library-based implementation that can match the productivity and performance of a compiler-based approach. We implement the array library as an extension to UPC++, a C++library for PGAS programs, and we extend Titanium arrays with specializations to improve performance. We evaluate the array library by porting four Titanium benchmarks to UPC++, demonstrating that it can achieve up to 25% better performance than Titanium without a significant increase in programmer effort..

Kamil, A↗

Enabling Pulse-level Programming, Compilation, and Execution in XACC

Noisy gate-model quantum processing units (QPUs) are currently available from vendors over the cloud, and digital quantum programming approaches exist to run low-depth circuits on physical hardware. These digital representations are ultimately lowered to pulse-level instructions by vendor quantum control systems to affect unitary evolution representative of the submitted digital circuit. Vendors are beginning to open this pulse-level control system to the public via specified interfaces. Robust programming methodologies, software frameworks, and backend simulation technologies for this analog model of quantum computation will prove critical to advancing pulse-level control research and development. Prototypical use cases for this include error mitigation, optimal pulse control, and physics-inspired pulse construction. Here we present an extension to the XACC quantum-classical software framework that enables pulse-level programming for superconducting, gate-model quantum computers, and a novel, general, and extensible pulse-level simulation backend for XACC that scales on classical compute clusters via MPI. Our work enables custom backend Hamiltonian definitions and gate-level compilation to available pulses with a focus on performance and scalability. We end with a demonstration of this capability, and show how to use XACC for pertinent pulse-level programming tasks.

97 MATHEMATICS AND COMPUTING↗

Improving Energy Efficiency of Air Separation via Hollow Fiber Sorbents

This report summarizes the work performed under the Department of Energy’s National Energy Technology Laboratory (DOE-NETL) Advanced Energy Systems Program award number DE-FE0026163 Improving Energy Efficiency of Air Separation via Hollow Fiber Sorbents. The overall objective of the project was to develop technology to produce oxygen for use in coal gasification processes at a significantly lower cost than that of the commercial state-of-the-art technology. The focus of the project was development and optimization of hollow fiber sorbents for use in a pressure swing adsorption (PSA) process for producing oxygen from air. The key technical advancement under this program was the development of a hollow fiber sorbent capable of producing oxygen in a PSA process. PSAs produce oxygen by using a beaded zeolite material (typically lithium exchanged zeolites or LiX) that selectively adsorb nitrogen over oxygen. For a fiber to adsorb nitrogen, LiX needed to be integrated into a polymer fiber and then activated at over 350C to remove residual moisture. After screening multiple materials and process techniques, Matrimid/LiX hollow fibers were produced that were able to withstand the activation and had crystalline nitrogen capacity close to pure LiX crystals. The fibers were dual layer fibers with a barrier layer isolating the hollow bore from the LiX embedded layer. The barrier layer was formed from an Ultem® based solution. The hollow bore was intended for encapsulating phase change materials to ensure isothermal PSA operation. Modeling work from the project suggested that the benefits of this additional complexity were marginal, thus the team fabricated non-hollow fibers comprised of Matrimid and LiX. The Matrimid/LiX fibers were loaded into a module and tested on a bench scale PSA unit. The fibers were able to separate oxygen from air, but the purity and recovery were lower than expected and lower than traditional beaded LiX zeolites, although modeling results suggested that the bed sizes for fiber sorbents could be half the size of a beaded LiX bed. Additional work will be needed to understand the shortfall and to produce fiber sorbent modules with performance equal to the targets set for this program. In addition to producing fibers, modeling work was carried out at both the fiber level and process level to guide both fiber sorbent development and to determine the optimal process conditions for a PSA using fiber sorbents. A 2D hollow fiber model was developed in gPROMS Model Builder. This model was based on literature data for mass transfer and other parameters. This model used a basic single bed PSA process to determine important fiber properties and process conditions for achieving high oxygen recovery. The preliminary 2D fiber model was a valuable tool, however, for step-out technologies, such as a PSA process with fiber sorbents, intelligent optimization and plant control was needed to effectively determine minimum power designs. Therefore, a gPROMS Process Builder-based optimization tool was developed with an “Automated Cycle Optimizer” model that was able to determine optimal cycle conditions for a fiber sorbent PSA. The results from the optimizer were used in the final power analysis. Flow sheet analysis and techno-economic analysis (TEA) was carried out to determine a lower power solution versus the baseline case. The original project scope suggested that the fiber sorbent PSA could be used to debottleneck a cryogenic air separation plant (cryo-ASU) with the combined plant having lower power than a standalone cryo-ASU. However, early flowsheet analysis showed that the PSA/cryo-ASU concept would not lead to a lower power solution. However, further flowsheet analysis suggested that an oxygen PSA combined with a nitrogen PSA could have lower power versus state-of-the-art air separation technology. Work concluded with the TEA showing a fiber sorbent oxygen PSA combined with an advanced nitrogen PSA could be up to 8% lower power versus the base case cryo-ASU. Overall, there is significant potential remaining for the zeolite hollow fiber sorbent concept, and this project successfully identified -- and ultimately remedied -- many technical challenges associated with scale-up.

01 COAL, LIGNITE, AND PEAT↗

Training Population Optimization for Genomic Selection in Miscanthus

Miscanthus is a perennial grass with potential for lignocellulosic ethanol production. To ensure its utility for this purpose, breeding efforts should focus on increasing genetic diversity of the nothospecies Miscanthus × giganteus (M×g) beyond the single clone used in many programs. Germplasm from the corresponding parental species M. sinensis (Msi) and M. sacchariflorus (Msa) could theoretically be used as training sets for genomic prediction of M×g clones with optimal genomic estimated breeding values for biofuel traits. To this end, we first showed that subpopulation structure makes a substantial contribution to the genomic selection (GS) prediction accuracies within a 538-member diversity panel of predominately Msi individuals and a 598-member diversity panels of Msa individuals. We then assessed the ability of these two diversity panels to train GS models that predict breeding values in an interspecific diploid 216-member M×g F2 panel. Low and negative prediction accuracies were observed when various subsets of the two diversity panels were used to train these GS models. To overcome the drawback of having only one interspecific M×g F2 panel available, we also evaluated prediction accuracies for traits simulated in 50 simulated interspecific M×g F2 panels derived from different sets of Msi and diploid Msa parents. The results revealed that genetic architectures with common causal mutations across Msi and Msa yielded the highest prediction accuracies. Ultimately, these results suggest that the ideal training set should contain the same causal mutations segregating within interspecific M×g populations, and thus efforts should be undertaken to ensure that individuals in the training and validation sets are as closely related as possible.

59 BASIC BIOLOGICAL SCIENCES↗