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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 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

HCOO - aq Degradation in Droplets by OH aq in an Atmospheric Pressure Glow Discharge

Plasmas in contact with liquids can degrade organic molecules in solution, as reactive oxygen and nitrogen species produced in the plasma solvate into the liquid. Immersing small droplets (tens of microns in diameter) in the plasma can more rapidly activate the liquid compared to treating a large volume of liquid with a smaller surface-to-volume ratio. The interactions between a radio frequency glow discharge sustained in He/H 2 O and a water droplet containing formate (HCOO - aq ) immersed in and flowing through the plasma were modeled using a 0-dimensional global plasma chemistry model to investigate these activation processes. HCOO - aq interacts with OH aq , produced from solvation of OH from the gas phase. HCOO - aq concentrations were benchmarked with previously reported experimental measurements. The diameter of the droplet, initial HCOO - aq concentration, and gas flow rate affect only the HCOO - aq concentration and OH aq density, leaving the OH density in the gas phase unaffected. Power deposition and gas mixture (e.g., percentage of H 2 O) change both the gas and liquid phase chemistry. A general trend was observed – during the first portion of droplet exposure to the plasma, OH aq primarily consumes HCOO - aq . However, O2 - aq , a byproduct of HCOO - aq consumption, consumes OH aq once O2 - aq reaches a critically large density. Using HCOO - aq as a surrogate for OH aq sensitive contaminants, combinations of residence time, droplet diameter, water vapor density, and power will determine the optimum remediation strategy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Binder-Coated Carbon Cloth Electrodes for All-Vanadium Redox Flow Batteries

Vanadium redox flow batteries (VRFBs) are a promising solution for integrating intermittent renewable energy sources into the existing power grid. However, enhancing the electrochemical performance of VRFBs is critical for their widespread adoption in grid-scale energy storage. This study investigates the impact of adding a porous binder to a carbon-cloth electrode, with a focus on optimizing thermal activation conditions. The electrochemical performance of the binder-coated electrodes compared to uncoated electrodes is evaluated through electrochemical impedance spectroscopy, polarization curve measurements, and charge-discharge cycling. The surface morphology and structural integrity of the binder-coated electrodes at each activation stage are examined using various material characterization techniques to assess the effects of thermal activation. The results are benchmarked against the experiments using non-coated electrodes to determine the performance improvements offered by the binder coating. Notably, the study reveals that binder-coated electrodes exhibit significantly lower resistance and improved efficiency compared to their uncoated counterparts, with optimal activation conditions enhancing performance metrics crucial for VRFB applications. These findings provide valuable insights for further optimizing electrode design and activation strategies, advancing the development of more efficient VRFB systems for large-scale energy storage.

Caiado, Ashley A.↗
DOE OSTI2018

Establishing a commercial building energy data framework for India

Buildings account for over 40% of the world’s energy consumption and are therefore a key contributor to a country’s energy as well as carbon budget. Understanding how buildings use energy is critical to understanding how related policies may impact energy use. Data enables decision making, and good quality data arms consumers with the tools to compare their energy performance to their peers, allowing them to differentiate their buildings in the real estate market on the basis of their energy footprint. Good quality data are also essential for policy makers to prioritize their energy saving strategies and track implementation. The United States’ Commercial Building Energy Consumption Survey (CBECS) is an example of a successful data framework that is highly useful for governmental and nongovernmental initiatives related to benchmarking energy forecasting, rating systems and metrics, and more. The Bureau of Energy Efficiency (BEE) in India developed the Energy Conservation Building Code (ECBC) and launched the Star Labeling program for a few energy-intensive building segments as a significant first step. However, a data driven policy framework for systematically targeting energy efficiency in both new construction and existing buildings has largely been missing. There is no quantifiable mechanism currently in place to track the impact of code adoption through regular reporting/survey of energy consumption in the commercial building stock. In this paper we present findings from our study that explored use cases and approaches for establishing a commercial buildings data framework for India.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Femtosecond Reflectance Spectroscopy for Energetic Material Diagnostics

Understanding the fundamental mechanisms underpinning shock initiation is critical to predicting energetic material (EM) safety and performance. Currently, the timescales and pathways by which shock-excited lattice modes transfer energy into specific chemical bonds remains an open question. Towards understanding these mechanisms, our group has previously measured the vibrational energy transfer (VET) pathways in several energetic thin films using broadband, femtosecond transient absorption spectroscopy. However, new technologies are needed to move beyond these thin film surrogates and measure broadband VET pathways in realistic EM morphologies. Herein, we describe a new broadband, femtosecond, attenuated total reflectance spectroscopy apparatus. Performance of the system is benchmarked against published data and the first VET results from a pressed EM pellet are presented. This technology enables fundamental studies of VET dynamics across sample configurations and environments (pressure, temperature, etc .) and supports the potential use of VET studies in the non-destructive surveillance of EM components.

42 ENGINEERING↗
NASA NTRS1989

An evaluative model of system performance in manned teleoperational systems

Manned teleoperational systems are used in aerospace operations in which humans must interact with machines remotely. Manual guidance of remotely piloted vehicles, controling a wind tunnel, carrying out a scientific procedure remotely are examples of teleoperations. A four input parameter throughput (Tp) model is presented which can be used to evaluate complex, manned, teleoperations-based systems and make critical comparisons among candidate control systems. The first two parameters of this model deal with nominal (A) and off-nominal (B) predicted events while the last two focus on measured events of two types, human performance (C) and system performance (D). Digital simulations showed that the expression A(1-B)/C+D) produced the greatest homogeneity of variance and distribution symmetry. Results from a recently completed manned life science telescience experiment will be used to further validate the model. Complex, interacting teleoperational systems may be systematically evaluated using this expression much like a computer benchmark is used.

Haines, Richard F.↗
NASA NTRS2010

Core-Noise

This presentation is a technical progress report and near-term outlook for NASA-internal and NASA-sponsored external work on core (combustor and turbine) noise funded by the Fundamental Aeronautics Program Subsonic Fixed Wing (SFW) Project. Sections of the presentation cover: the SFW system level noise metrics for the 2015, 2020, and 2025 timeframes; the emerging importance of core noise and its relevance to the SFW Reduced-Noise-Aircraft Technical Challenge; the current research activities in the core-noise area, with some additional details given about the development of a high-fidelity combustion-noise prediction capability; the need for a core-noise diagnostic capability to generate benchmark data for validation of both high-fidelity work and improved models, as well as testing of future noise-reduction technologies; relevant existing core-noise tests using real engines and auxiliary power units; and examples of possible scenarios for a future diagnostic facility. The NASA Fundamental Aeronautics Program has the principal objective of overcoming today's national challenges in air transportation. The SFW Reduced-Noise-Aircraft Technical Challenge aims to enable concepts and technologies to dramatically reduce the perceived aircraft noise outside of airport boundaries. This reduction of aircraft noise is critical for enabling the anticipated large increase in future air traffic. Noise generated in the jet engine core, by sources such as the compressor, combustor, and turbine, can be a significant contribution to the overall noise signature at low-power conditions, typical of approach flight. At high engine power during takeoff, jet and fan noise have traditionally dominated over core noise. However, current design trends and expected technological advances in engine-cycle design as well as noise-reduction methods are likely to reduce non-core noise even at engine-power points higher than approach. In addition, future low-emission combustor designs could increase the combustion-noise component. The trend towards high-power-density cores also means that the noise generated in the low-pressure turbine will likely increase. Consequently, the combined result from these emerging changes will be to elevate the overall importance of turbomachinery core noise, which will need to be addressed in order to meet future noise goals.

Hultgren, Lennart S.↗
DOE OSTI2021

State predictive information bottleneck

We report the ability to make sense of the massive amounts of high-dimensional data generated from molecular dynamics simulations is heavily dependent on the knowledge of a low-dimensional manifold (parameterized by a reaction coordinate or RC) that typically distinguishes between relevant metastable states, and which captures the relevant slow dynamics of interest. Methods based on machine learning and artificial intelligence have been proposed over the years to deal with learning such low-dimensional manifolds, but they are often criticized for a disconnect from more traditional and physically interpretable approaches. To deal with such concerns, in this work we propose a deep learning based state predictive information bottleneck approach to learn the RC from high-dimensional molecular simulation trajectories. We demonstrate analytically and numerically how the RC learnt in this approach is connected to the committor in chemical physics and can be used to accurately identify transition states. A crucial hyperparameter in this approach is the time delay or how far into the future the algorithm should make predictions about. Through careful comparisons for benchmark systems, we demonstrate that this hyperparameter choice gives useful control over how coarse-grained we want the metastable state classification of the system to be. We thus believe that this work represents a step forward in systematic application of deep learning based ideas to molecular simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Influence of the drive design on ablation front hydrodynamic instability growth in a capsule implosion at the National Ignition Facility

A critical aspect of inertial confinement fusion experiments lies in the control of ablation front instabilities during the implosion process. The growth of Rayleigh–Taylor and Richtmyer–Meshkov instabilities, seeded by target defects, can significantly degrade the performance of the implosion. Here, this study explores the influence of drive design on ablation front stability using the hydro-growth radiography platform at the National Ignition Facility. This platform allows the measurement of the ablation front hydrodynamic instability growth. Because these measurements are restricted to early convergence, their primary role is to constrain the initial instability growth and benchmark the simulations used to infer shell integrity and performance at peak velocity and ignition. Three ignition designs, Hybrid-E (HyE), SQ-n (“S” for scaling and “Q” for quality), and High temperature, High thickness (HiT) were analyzed. The results demonstrated a high dependence of the growth factor on the choice of design, capsule scale as well as the hohlraum conditions, mainly the radiative temperature and the gold M-band emission. HyE and SQ-n display a similar growth factor range, but their evolution is different due to the design differences in hohlraum conditions. HiT has the lowest growth factor of the studied designs, which is a result of a higher radiative temperature. These results highlight the importance of design choices in controlling instability dynamics. These insights inform future drive design strategies to enhance stability and efficiency in fusion ignition experiments.

Physics↗
DOE OSTI2025

I/O in Machine Learning Applications on HPC Systems: A 360-degree Survey

Growing interest in Artificial Intelligence (AI) has resulted in a surge in demand for faster methods of Machine Learning (ML) model training and inference. This demand for speed has prompted the use of high performance computing (HPC) systems that excel in managing distributed workloads. Because data is the main fuel for AI applications, the performance of the storage and I/O subsystem of HPC systems is critical. In the past, HPC applications accessed large portions of data written by simulations or experiments or ingested data for visualizations or analysis tasks. ML workloads perform small reads spread across a large number of random files. This shift of I/O access patterns poses several challenges to modern parallel storage systems. In this paper, we survey I/O in ML applications on HPC systems, and target literature within a 6-year time window from 2019 to 2024. We define the scope of the survey, provide an overview of the common phases of ML, review available profilers and benchmarks, examine the I/O patterns encountered during offline data preparation, training, and inference, and explore I/O optimizations utilized in modern ML frameworks and proposed in recent literature. Lastly, we seek to expose research gaps that could spawn further R&D.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1983

Shuttle orbiter boundary layer transition at flight and wind tunnel conditions

Hypersonic boundary layer transition data obtained on the windward centerline of the Shuttle orbiter during entry for the first five flights are presented and analyzed. Because the orbiter surface is composed of a large number of thermal protection tiles, the transition data include the effects of distributed roughness arising from tile misalignment and gaps. These data are used as a benchmark for assessing and improving the accuracy of boundary layer transition predictions based on correlations of wind tunnel data taken on both aerodynamically rough and smooth orbiter surfaces. By comparing these two data bases, the relative importance of tunnel free stream noise and surface roughness on orbiter boundary layer transition correlation parameters can be assessed. This assessment indicates that accurate predications of transition times can be made for the orbiter at hypersonic flight conditions by using roughness dominated wind tunnel data. Specifically, times of transition onset and completion is accurately predicted using a correlation based on critical and effective values of a roughness Reynolds number previously derived from wind tunnel data.

Goodrich, W. D.↗
NASA NTRSDate not supplied

Traffic Prediction for Uncommunicative Aircraft in Terminal Airspace: Development Framework and Performance Evaluations

This paper presents an air traffic prediction algorithm that takes observations of an aircraft and classifies aircraft type, estimates the aircraft's intent to and method of joining an airport traffic pattern, and predicts the aircaft's future trajectory. To develop algorithms that enable autonomous aircraft to safely insert into un-towered traffic patterns, several challenges need to be addressed. These challenges range from traffic detection to sensor fusion to own-ship trajectory replanning. Critical to a trajectory replanning algorithm is information regarding the future behavior of all traffic aircraft in the operational environment. The presented traffic prediction algorithm generates this information using regular measurements of traffic aircraft position and velocity to classify the aircraft by speed-class, estimate how the aircraft will approach the runway, and construct a predicted trajectory to the runway including future positions and velocities at specific times. The predictions of the presented algorithm are the necessary inputs for any downstream traffic pattern sequencing and own-ship trajectory planning routines. The presented algorithm is benchmarked using approximately 300 randomized traffic trajectories, spanning four vehicle weight classes and eight traffic entry types. While the algorithm can process multiple traffic vehicles in the terminal area, there is no prediction of traffic-on-traffic interaction. Each traffic vehicle is processed separately.

John D McMinn↗
DOE OSTI2017

Performance of fully-coupled algebraic multigrid preconditioners for large-scale VMS resistive MHD

Here, we explore the current performance and scaling of a fully-implicit stabilized unstructured finite element (FE) variational multiscale (VMS) capability for large-scale simulations of 3D incompressible resistive magnetohydrodynamics (MHD). The large-scale linear systems that are generated by a Newton nonlinear solver approach are iteratively solved by preconditioned Krylov subspace methods. The efficiency of this approach is critically dependent on the scalability and performance of the algebraic multigrid preconditioner. Our study considers the performance of the numerical methods as recently implemented in the second-generation Trilinos implementation that is 64-bit compliant and is not limited by the 32-bit global identifiers of the original Epetra-based Trilinos. The study presents representative results for a Poisson problem on 1.6 million cores of an IBM Blue Gene/Q platform to demonstrate very large-scale parallel execution. Additionally, results for a more challenging steady-state MHD generator and a transient solution of a benchmark MHD turbulence calculation for the full resistive MHD system are also presented. These results are obtained on up to 131,000 cores of a Cray XC40 and one million cores of a BG/Q system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Passive and active neutron signatures of 233 U for nondestructive assay

The thorium fuel cycle is emerging as an attractive alternative to conventional nuclear fuel cycles, as it does not require the enrichment of uranium for long-term sustainability. The operating principle of this fuel cycle is the irradiation of 232 Th to produce 233 U, which is fissile and sustains the fission chain reaction. 233 U poses unique challenges for nuclear safeguards, as it is associated with a uniquely extreme γ-ray environment from 232 U contamination, which limits the feasibility of the γ-ray-based assay, as well as more conservative accountability requirements than for 235 U set by the International Atomic Energy Agency. Consequently, instrumentation used for safeguarding 235 U in traditional fuel cycles may be inapplicable. It is essential that the nondestructive signatures of 233 U be characterized so that nuclear safeguards can be applied to thorium fuel-cycle facilities as they come online. In this work, a set of 233 U 3 O 8 plates, containing 984 g 233 U, was measured at the National Criticality Experiments Research Center. A high-pressure 4 He gaseous scintillation detector, which is insensitive to γ-rays, was used to perform a passive fast neutron spectral signature measurement of 233 U 3 O 8 , and was used in conjunction with a pulsed deuterium-tritium neutron generator to demonstrate the differential die-away signature of this material. Furthermore, an array of 3 He detectors was used in conjunction with the same neutron generator to measure the delayed neutron time profile of 233 U, which is unique to this nuclide. These measurements provide a benchmark for future nondestructive assay instrumentation development, and demonstrate a set of key neutron signatures to be leveraged for nuclear safeguards in the thorium fuel cycle.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Deep Reinforcement Learning Enabled Physical-Model-Free Two-Timescale Voltage Control Method for Active Distribution Systems

Active distribution networks are being challenged by frequent and rapid voltage violations due to renewable energy integration. Conventional model-based voltage control methods rely on accurate parameters of the distribution networks, which are difficult to achieve in practice. This paper proposes a novel physical-model-free two-timescale voltage control framework for active distribution systems. To achieve fast control of PV inverters, the whole network is first partitioned into several subnetworks using voltage-reactive power sensitivity. Then, the scheduling of PV inverters in the multiple sub-networks is formulated as Markov games and solved by a multi-agent soft actor-critic (MASAC) algorithm, where each subnetwork is modeled as an intelligent agent. All agents are trained in a centralized manner to learn a coordinated strategy while being executed based on only local information for fast response. For the slower time-scale control, OLTCs and switched capacitors are coordinated by a single agent-based SAC algorithm using the global information with considering control behaviors of the inverters. Particularly, the two-level agents are trained concurrently with information exchange according to the reward signal calculated from the data-driven surrogate model. Comparative tests with different benchmark methods on IEEE 33-and 123-bus systems and 342-node low voltage distribution system demonstrate that the proposed method can effectively mitigate the fast voltage violations and achieve systematical coordination of different voltage regulation assets without the knowledge of accurate system model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Implications of Upwells as Hydrodynamic Jets in a Pulse Jet Mixed System

This report evaluates the physics of the upwell flow in pulse jet mixed systems in the Hanford Tank Waste Treatment and Immobilization Plant (WTP). Although the initial downward flow and radial flow from pulse jet mixers (PJMs) has been analyzed in some detail, the upwells have received considerably less attention despite having significant implications for vessel mixing. Do the upwells behave like jets? How do the upwells scale? When will the central upwell breakthrough? What proportion of the vessel is blended by the upwells themselves? Indeed, how the physics of the central upwell is affected by multiple PJMs (e.g., six in the proposed mixing vessels), non-Newtonian rheology, and significant multicomponent solids loadings remain unexplored. The central upwell must satisfy several criteria to be considered a free jet. First, it must travel for several diameters in a nearly constant direction. Second, its velocity must decay with the inverse of elevation. Third, it should have an approximately Gaussian profile. Fourth, the influence of surface or body forces must be negligible. A combination of historical data in a 12.75 ft test vessel, newly analyzed data from the 8 ft test vessel, and conservation of momentum arguments derived specifically for PJM operating conditions demonstrate that the central upwell satisfies these criteria where vigorous breakthrough is achieved. An essential feature of scaling from one vessel to the next is the requirement that the underlying physics does not change adversely. One may have confidence in scaling if (1) correlations and formulas capture the relevant physics; (2) the underlying physics does not change from the conditions under which it was developed to the conditions of interest; (3) all factors relevant to scaling have been incorporated, including flow, material, and geometric considerations; and (4) the uncertainty in the relationships is sufficiently narrow to meet required specifications. Although the central upwell satisfies these criteria when vigorous breakthrough is achieved, not all available data follow the free jet profile for the central upwell, particularly at lower nozzle velocities. Alternative flow regimes are considered and new models for cloud height, “cavern height,” and the rate of jet penetration (jet celerity) are benchmarked against data to anchor scaling analyses. This analytical modeling effort to provide a technical basis for scaling PJM mixed vessels has significant implications for vessel mixing, because jet physics underlies “cavern” height, cloud height, and the volume of mixing considerations. A new four-parameter cloud height model compares favorably to experimental results. This model is predictive of breakthrough in 8 ft vessel tests with the two-part simulant. Analysis of the upwell in the presence of yield stresses finds evidence of expanding turbulent jets, confined turbulent jets, and confined laminar flows. For each, the critical elevation at which jet momentum depletes is predicted, which compare favorably to experimental cavern height data. Partially coupled momentum and energy balances suggest that these are limiting cases of a gradual transition from a turbulent expanding flow to a confined laminar flow. This analysis of the central upwell alone lays essential groundwork for complete analysis of mode three mixing (i.e., breakthrough with slow peripheral mixing). Consideration of jet celerity shows that the rate of jet penetration is a governing consideration in breakthrough to the surface. Estimates of the volume of mixing are presented. This analysis shows that flow along the vessel wall is sluggish such that the central upwell governs the volume of mixing. This analysis of the central upwell alone lays essential groundwork for complete analysis of mode three mixing and estimates of hydrogen release rates from first principles.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Preliminary Two-Phase Terry Turbine Nozzle Models for RCIC Off-Design Operation Conditions

This report presents the effort to extend the single-phase analytical Terry turbine model to cover two-phase off-design conditions. The work includes: (1) adding well-established two-phase choking models – the Isentropic Homogenous Equilibrium Model (IHEM) and Moody’s model, and (2) theoretical development and implementation of a two-phase nozzle expansion model. The two choking models provide bounding cases for the two-phase choking mass flow rate. The new two-phase Terry turbine model uses the choking models to calculate the mass flow rate, the critical pressure at the nozzle throat, and steam quality. In the divergent stage, we only consider the vapor phase with a similar model for the single-phase case by assuming that the liquid phase would slip along the wall with a much slower speed and will not contribute the impulse on the rotor. We also modify the stagnation conditions according to two-phase choking conditions at the throat and the cross-section areas for steam flow at the nozzle throat and at the nozzle exit. The new two-phase Terry turbine model was benchmarked with the same steam nozzle test as for the single-phase model. Better agreement with the experimental data is observed than from the single-phase model. We also repeated the Terry turbine nozzle benchmark work against the Sandia CFD simulation results with the two-phase model for the pure steam inlet nozzle case. The RCIC start-up tests were simulated and compared with the single-phase model. Similar results are obtained. Finally, we designed a new RCIC system test case to simulate the self-regulated Terry turbine behavior observed in Fukushima accidents. In this test, a period inlet condition for the steam quality varying from 1 to 0 is applied. For the high quality inlet period, the RCIC system behaves just like the normal operation condition with a high pump injection flow rate and a nominal steam release rate through the turbine, with the net addition of water to the primary system; for the low quality inlet period, the RCIC turbine shaft work dramatically decreases and results in a much reduced pump injection flow rate, and the mixture flow rate through the turbine increases due to the high liquid phase flow rate. The net effect for this period is net removal of coolant from the primary loop. With the periodic addition and removal of coolant to the primary loop, the self-regulation mode of the RCIC system can be maintained for a quite long time. Both the IHEM and Moody’s models generate similar phenomena; however noticeable differences can be observed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

MPACT Verification and Validation Manual (rev 1)

The MPACT code provides the capability to calculate the steady-state and transient reactor core neutron distribution for operating nuclear power plant (PWR) conditions across multiple fuel cycles. As required in the CASL SQA plan, it is the responsibility of UM and ORNL as joint owners of MPACT to ensure that verification and validation activities are performed and documented in a V&V manual with supporting publications and CASL technical reports which can be distributed for reference and distribution within VERA. This document provides the first revision of the MPACT verification and validation (V&V) manual and describes the current state of MPACT V&V and updates the framework for future MPACT V&V activities. During FY16, MPACT V&V activities in the areas of code verification have continued to mature and work has progressed on code error evaluation using the Method of Manufactured Solutions (MMS). Several specific tasks have also been completed to improve MPACT code verification to include tasks to improve the unit and regression test coverage. A joint UM/ORNL task was completed to develop standardize coding standards and workflow for the continued collaborative development of MPACT. During the past year, MPACT validation work has continued in both the areas of measured data from critical experiments as well as measured data from operating nuclear power plants. Preliminary work was also performed in FY16 on the use of post-irradiation examinations for evaluation and validation of the isotopic depletion capability in MPACT. Based on the results of V&V efforts this past year, the confidence level has increased in the ability of MPACT to model an operational Pressurized Water Reactor. Areas were identified which require increased emphasis during FY17 to include updating all the V&V problems with the new 51-group library, the completion of cycle 2 of the BEAVRS benchmark, initial validation for BWR applications, the addition of Uncertainty Quantification results into the benchmark results, and the completion of specific validation tasks for the CASL Challenge problems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Complex relationship between seasonal streamflow forecast skill and value in reservoir operations

Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts) to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strong relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made – namely during severe drought. As it is not possible to know in advance if a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.

42 ENGINEERING↗