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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Computer-aided analysis and design of the shape rolling process for producing turbine engine airfoils

Mild steel (AISI 1018) was selected as model cold-rolling material and Ti-6Al-4V and INCONEL 718 were selected as typical hot-rolling and cold-rolling alloys, respectively. The flow stress and workability of these alloys were characterized and friction factor at the roll/workpiece interface was determined at their respective working conditions by conducting ring tests. Computer-aided mathematical models for predicting metal flow and stresses, and for simulating the shape-rolling process were developed. These models utilize the upper-bound and the slab methods of analysis, and are capable of predicting the lateral spread, roll-separating force, roll torque and local stresses, strains and strain rates. This computer-aided design (CAD) system is also capable of simulating the actual rolling process and thereby designing roll-pass schedule in rolling of an airfoil or similar shape. The predictions from the CAD system were verified with respect to cold rolling of mild steel plates. The system is being applied to cold and hot isothermal rolling of an airfoil shape, and will be verified with respect to laboratory experiments under controlled conditions.

Lahoti, G. D.↗
DOE OSTI2021

Quantifying the structural uncertainty of the aerosol mixing state representation in a modal model

Abstract. Aerosol mixing state is an important emergent property that affects aerosol radiative forcing and aerosol–cloud interactions, but it has not been easy to constrain this property globally. This study aims to verify the global distribution of aerosol mixing state represented by modal models. To quantify the aerosol mixing state, we used the aerosol mixing state indices for submicron aerosol based on the mixing of optically absorbing and non-absorbing species (χo), the mixing of primary carbonaceous and non-primary carbonaceous species (χc), and the mixing of hygroscopic and non-hygroscopic species (χh). To achieve a spatiotemporal comparison, we calculated the mixing state indices using output from the Community Earth System Model with the four-mode version of the Modal Aerosol Module (MAM4) and compared the results with the mixing state indices from a benchmark machine-learned model trained on high-detail particle-resolved simulations from the particle-resolved stochastic aerosol model PartMC-MOSAIC. The two methods yielded very different spatial patterns of the mixing state indices. In some regions, the yearly averaged χ value computed by the MAM4 model differed by up to 70 percentage points from the benchmark values. These errors tended to be zonally structured, with the MAM4 model predicting a more internally mixed aerosol at low latitudes and a more externally mixed aerosol at high latitudes compared to the benchmark. Our study quantifies potential model bias in simulating mixing state in different regions and provides insights into potential improvements to model process representation for a more realistic simulation of aerosols towards better quantification of radiative forcing and aerosol–cloud interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

AM Modeling & Simulation

A predictive simulation capability for AM is important to improve quality, decrease processing time and minimize costs. Has significant impact as LANL continues to be a leader in modeling and simulation for AM. This improved simulation capability will allow important AM specific physics questions to be answered for the first time. This approach, in combination with LANL's HPC resources will enable tractable, predictive simulation of AM and other solidification processes.

42 ENGINEERING↗
DOE OSTI2023

Exploiting electricity market dynamics using flexible electrolysis units for retrofitting methanol synthesis

Here we investigate the economic viability of integrating flexible electrolysis units to produce hydrogen in methanol synthesis processes. Specifically, we investigate whether this approach can help reduce methanol production costs by strategically exploiting dynamics of electricity markets. Our study integrates high-fidelity process simulations, optimization tools, and microkinetic modeling (informed by density functional theory) to conduct detailed techno-economic analyses and to compare performance against traditional processes that use hydrogen produced via steam-methane reforming (SMR). We also use this approach to estimate the levelized cost of hydrogen (LCOH) as a function of time-varying electricity prices (from day-ahead and real-time prices) and of key techno-economic parameters. Our results show that the proposed electrification framework is cost-competitive under certain electricity market conditions. Specifically, we find that, when the electrolysis system is operated in flexible mode (and can respond to dynamics of electricity markets), the associated electricity cost nearly collapses to zero. Conversely, when the unit is not flexible (and cannot respond to markets), the electricity cost comprises 60% of the total cost. Our results also reveal that the LCOH of the flexible electrolysis system participating in real-time electricity markets is 31% lower than the LCOH obtained from SMR. Overall, this indicates that exploiting the dynamics of electricity markets can make hydrogen production cost-competitive and this can lead to viable alternatives to electrify methanol production and other hydrogen-based processes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1992

Combustion of LOX with H2(sub g) under subcritical, critical, and supercritical conditions and experimental observation of dense spray and mixing of impinging jets

Progress made during the period of February 1 to October 15, 1992 is reported. The overall objective of Task 1 of the investigation is to achieve a better understanding of the combustion processes of liquid oxygen and gaseous hydrogen under subcritical, critical, and supercritical conditions. Specific objectives of the research program are: (1) to determine the evaporation- and burning-rate characteristics of LOX in hydrogen/helium environments under broad ranges of operating conditions; (2) to measure species concentration profile and surface temperature of LOX employing the gas chromatography and fine-wire thermocouples under non-reacting flow situations; (3) to perform a fugacity-based multicomponent thermodynamic phase equilibrium analysis for examining the high-pressure vapor-liquid equilibrium behavior at the liquid surface of LOX; (4) to formulate and solve a theoretical model for simulating the evaporation and combustion processes in a LOX/H2/He system; and (5) to validate the theoretical model with the measured experimental data. Task 2 of the investigation is described. Observation of a like-on-like injector element in the near-injector region performed in the previous phase of this project has identified the existence of a high Reynolds number regime in which the pre-impingement jets are fully turbulent and undergoing surface breakup. The new spray regime, which has not been observed by previous investigators, is characterized by the presence of many fine droplets and the disappearance of the well-defined liquid breakup wave pattern in the post-impingement region. It is speculated that a cavitating region may be present within the orifice so that it could induce strong turbulence, leading to an onset of atomization of the jets prior to impingement. To further investigate the dense spray behavior of the impinging jets in the high Reynolds number region, experiments were conducted using Plexiglas injector components for direct internal flow observation. The main objective is to determine under what conditions a cavitating region would form and whether or not the cavitation is reponsible for the development of the high Reynolds number spray regime. The procedure and major findings of the injector cavitation study are described.

Kuo, Kenneth K.↗
NASA NTRS2013

Simulation of Inflated Pahoehoe Lava Flows

A new stochastic model simulates late-stage pahoehoe lobes where random processes dominate emplacement. The model prescribes probabilistic rules for determining where and when parcels of lava move within the lobe. Unlike a classical Brownian motion random walk, the model allows individual parcels to remain dormant, but fluid, for multiple time steps. The randomness of parcel volume transfers within the lobe interior as well as at the margins qualitatively reflects inflation processes observed in the field. The fraction of inflated volume to total volume increases with the total volume, with greater than 75% of the lobe volume contributed through inflation for typical lobes. The influence on planform shape and topographic cross-sectional profiles of total volume, source area and shape, topographic confinement, and sequential breakouts at the lobe margins, are all explored with the stochastic model. Each of these factors influences the overall lobe thickness and width. The model provides a means for assessing the relative importance of these processes through comparisons with field data. For the first time, Gaussian and parabolic functions are quantitatively fit to field measurements of pahoehoe lobes. Both functional forms provide adequate description of the cross-sectional flow shapes. When comparing simulated lobes to field data, sequential breakouts at the lobe margins are found to be an important process controlling the final topographic distribution of observed pahoehoe lobes.

modeling↗
NASA NTRS1998

Status of and Outlook for Largescale Modeling of Atmosphere-Ice-Ocean Interactions in the Arctic

Arctic air masses have direct impacts on the weather and climatic extremes of midlatitude areas such as central North America. Arctic physical processes pose special and very important problems for global atmospheric models used for climate simulation and numerical weather prediction. At present, the observational database is inadequate to support research aimed at overcoming these problems. Three interdependent Arctic field programs now being planned will help to remedy this situation: SHEBA, which will operate an ice camp in the Arctic for a year-, ARM, which will supply instruments for use at the SHEBA ice camp and which will also conduct longer-term measurements near Barrow, Alaska; and FIRE, which will conduct one or more aircraft campaigns, in conjunction with remote-sensing investigations focused on the SHEBA ice camp. This paper provides an introductory overview of the physics of the Arctic from the perspective of large-scale modelers, outlines some of the modeling problems that arise in attempting to simulate these processes, and explains how the data to be provided by the three field programs can be used to test and improve large-scale models.

Randall, David↗
DOE OSTI2024

Convergence in simulating global soil organic carbon by structurally different models after data assimilation

Abstract Current biogeochemical models produce carbon–climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage. Two structurally different models featuring distinctive carbon pools, decomposition kinetics, and carbon transfer pathways simulate opposite global SOC distributions with their customary parameter values yet converge to similar results after being informed by the same global SOC database using a data assimilation approach. The converged spatial SOC simulations result from similar simulations in key model components such as carbon transfer efficiency, baseline decomposition rate, and environmental effects on carbon fluxes by these two models after data assimilation. Moreover, data assimilation results suggest equally effective simulations of SOC using models following either first‐order or Michaelis–Menten kinetics at the global scale. Nevertheless, a wider range of data with high‐quality control and assurance are needed to further constrain SOC dynamics simulations and reduce unconstrained parameters. New sets of data, such as microbial genomics‐function relationships, may also suggest novel structures to account for in future model development. Overall, our results highlight the importance of observational data in informing model development and constraining model predictions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

Combining Livestock Production Information in a Process-Based Vegetation Model to Reconstruct the History of Grassland Management

Grassland management type (grazed or mown) and intensity (intensive or extensive) play a crucial role in the greenhouse gas balance and surface energy budget of this biome, both at field scale and at large spatial scale. However, global gridded historical information on grassland management intensity is not available. Combining modelled grass-biomass productivity with statistics of the grass-biomass demand by livestock, we reconstruct gridded maps of grassland management intensity from 1901 to 2012. These maps include the minimum area of managed vs. maximum area of unmanaged grasslands and the fraction of mown vs. grazed area at a resolution of 0.5deg by 0.5deg. The grass-biomass demand is derived from a livestock dataset for 2000, extended to cover the period 19012012. The grass-biomass supply (i.e. forage grass from mown grassland and biomass grazed) is simulated by the process-based model ORCHIDEE-GM driven by historical climate change, risingCO2 concentration, and changes in nitrogen fertilization. The global area of managed grassland obtained in this study increases from 6.1 x 10(exp 6) km(exp 2) in 1901 to 12.3 x 10(exp 6) kmI(exp 2) in 2000, although the expansion pathway varies between different regions. ORCHIDEE-GM also simulated augmentation in global mean productivity and herbage-use efficiency over managed grassland during the 20th century, indicating a general intensification of grassland management at global scale but with regional differences. The gridded grassland management intensity maps are model dependent because they depend on modelled productivity. Thus specific attention was given to the evaluation of modelled productivity against a series of observations from site-level net primary productivity (NPP) measurements to two global satellite products of gross primary productivity (GPP) (MODIS-GPP and SIF data). Generally, ORCHIDEE-GM captures the spatial pattern, seasonal cycle, and inter-annual variability of grassland productivity at global scale well and thus is appropriate for global applications presented here.

Livestock dataset↗
DOE OSTI2023

Advanced Drying Cycle Simulator Thermal Response to Commercial Drying Conditions

The purpose of this report is to document updates on testing of the apparatus built to simulate commercial drying procedures for spent nuclear fuel at the Nuclear Energy Work Complex at Sandia National Laboratories. Validation of the extent of water removal in a dry spent nuclear fuel storage system based on drying procedures used at nuclear power plants is needed to close existing technical gaps. Operational conditions leading to incomplete drying may have potential impacts on the fuel, cladding, and other components in the system during subsequent storage and disposal. A general lack of data suitable for model validation of commercial nuclear canister drying processes necessitates well-designed investigations of drying process efficacy and water retention that incorporate relevant physics and well-controlled boundary conditions. This report documents testing updates for the Advanced Drying Cycle Simulator (ADCS). This apparatus was built to simulate commercial drying procedures and quantify the amount of residual water remaining in a pressurized water reactor (PWR) fuel assembly after drying. The ADCS was constructed with a prototypic 17×17 PWR fuel skeleton and waterproof heater rods to simulate decay heat. These waterproof heaters are the next generation design to heater rods developed and tested at Sandia National Laboratories in FY20. This report describes preliminary testing of the ADCS through measurement and analysis of the thermal response of the system to a subset of commercial drying conditions that exclude the introduction of water, namely simulated decay heats and pressures relevant to commercial drying. This test series, referred to as a “dry” test series in this report, spans three uniform waterproof heater rod powers (representing spent fuel decay heats), four helium fill pressures, and six vacuum levels. This test series was conducted to cover the range of expected ADCS testing conditions for upcoming “wet” testing, where water will be introduced and a simulated commercial drying cycle will be performed. The dry test conditions were derived from the commercial drying conditions seen in the High Burnup Demonstration and the vacuum drying conditions chosen for a smaller scale Dashpot Drying Apparatus tested at Sandia National Laboratories in FY22. For a given uniform power and pressure/vacuum level, the ADCS was operated at constant power and pressure and allowed to reach steady state conditions. The thermal data obtained from these tests were analyzed, and the results can inform computational models built to simulate commercial drying processes by providing baseline thermal data prior to the introduction of water. Following the preliminary dry tests, a test plan for the ADCS will be developed to implement a drying procedure that begins with the introduction of water to the system and is based on measurements from the drying process used for the High Burnup Demonstration Project. While applying power to the simulated fuel rods, this procedure is expected to consist of filling the ADCS vessel with water, draining the water with applied pressure and multiple helium blowdowns, evacuating additional water with a vacuum drying sequence at successively lower pressures, and backfilling the vessel with helium. Additional investigations are expected to feature failed fuel rod simulators with engineered cladding defects and guide tubes with obstructed dashpots to challenge the drying system with multiple water retention sites. The data from these investigations is expected to inform the efficacy of commercial drying operations through the quantification of residual water in a prototypic-length dry storage canister.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Optical modeling of a radioisotope atmospheric chamber

Abstract Volatile radioisotopes represent a substantial health risk when released into the environment. To better understand the environmental fate of radioisotopes, the authors constructed a cylindrical steel-walled chamber to simulate the atmospheric processing of volatile radioactive gases. Optical modeling was performed for the properties of simulated sunlight in the chamber to better characterize atmospheric reaction studies. Optical simulations were performed using two wall materials (steel and thin-film silica) and validated against experimental measurements. This optical analysis methodology can be used to improve the fidelity of atmospheric models by accounting for optical inhomogeneities enabling a firmer grasp of radioisotopes’ environmental fate. Graphical abstract

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1991

Verification Of Tooling For Robotic Welding

Computer simulations, robotic inspections, and visual inspections performed to detect discrepancies. Method for verification of tooling for robotic welding involves combination of computer simulations and visual inspections. Verification process ensures accuracy of mathematical model representing tooling in off-line programming system that numerically simulates operation of robotic welding system. Process helps prevent damaging collisions between welding equipment and workpiece, ensures tooling positioned and oriented properly with respect to workpiece, and/or determines whether tooling to be modified or adjusted to achieve foregoing objectives.

Osterloh, Mark R.↗
DOE OSTI2021

A HPC Theory-Guided Machine Learning Cyberinfrastructure for Communicating Hydrometeorological Data Across Scales

High-resolution predictions of hydrometeorological variables are critical for supporting hydropower generation decisions and flood control at hydroelectric power plants. Traditional climate and hydrologic models rely on the numerical simulation of detailed physical processes. Therefore, running these simulations is time-, labor-, and computation-intensive. Improving the spatial and temporal resolution in these modeling outputs could lead to cubic increases in both the simulation time and computational demands, rendering high-resolution hydrometeorological predictions expensive and impractical. Many past studies apply the super resolution (SR) technique to downscale climate models using deep learners. However, deep learners are deemed “black-boxes,” as their derivation processes from low-resolution outputs to high-resolution outputs are often hidden. Their results are difficult for domain scientists to interpret and validate. Thus, there is a need for an exploratory machine learning approach that can partially integrate domain-specific theory and knowledge into the data-driven mapping process between simulation outputs of different spatial scales. The domain-specific theory and knowledge can be incorporated into the data model through an inductive approach in which process-related environmental variables are used and analyzed as key drivers (i.e., environmental surrogates) to reflect the complex physical processes. Many of these variables, such as land use land cover, soil types, topography, digital elevation, air temperature, and various watershed characteristics, can be directly measured through sensors or remote sensing techniques. Additionally, SR applications that can downscale hydrological and hydrodynamics models to efficiently produce high-resolution (1 m) flood depth grids are still rare. Since the flood depth grid can be used to support critical decisions for flood control operation at hydroelectric power plants, it is crucial to enable an SR-based capability for interpolating high-resolution flood inundation maps.

13 HYDRO ENERGY↗
DOE OSTI2025

Reduced Model of Ionization Lag in Intense Laser-Produced Plasmas

A physics-based empirical formula is derived to predict the ionization lag in underdense plasmas generated by an intense laser. Time-dependent nonlocal thermodynamic equilibrium calculations demonstrate significantly delayed ionization, due to rapid changes in plasma conditions, which critically impacts plasma properties such as opacity, emissivity, and heat transport. The reduced model, based on these calculations, enables the estimation of ionization lag without requiring in-depth knowledge of nonlocal thermodynamic equilibrium modeling. Furthermore, modeling reveals that the two-step ionization process—collisional excitation followed by photoionization—plays a crucial role in this ionization delay, with collisional excitation setting the timescale for ionization. Simulations across a range of elements, from beryllium to germanium, demonstrate that ionization lag is a widespread phenomenon, underscoring the importance of incorporating such processes into ionization modeling in radiation hydrodynamic simulations for various laser-plasma experiments.

direct drive↗
DOE OSTI2025

RSPECT: A PROSPECT-based model incorporating the real structure of rice leaves

Radiative transfer models (RTMs) describe how light is absorbed, scattered, and transmitted within leaves by simulating mechanistic light propagation processes. The PROSPECT model is based on measurable parameters (the leaf biochemical content) and a non-measurable parameter (the leaf anatomical structure represented by the leaf structure parameter (N)). The effect of N on the optical properties of leaves has been investigated through a number of local and global sensitivity analyses. Other studies have directly evaluated the effect of the leaf anatomical structure on spectral reflectance, particularly in the near infrared region. However, the relationship between N and the anatomical structure is unclear. Here, in this study, we leveraged eLeaf, a ray tracing-based 3D rice leaf simulator, to establish relationships between leaf anatomical features and spectral properties, enabling us to replace N in the PROSPECT-4 model with measurable leaf anatomical parameters and develop the RSPECT model. The leaf thickness at minor vein, leaf thickness at bulliform cells, mesophyll thickness at minor vein, and distance between two minor veins could be used to predict N effectively. The RSPECT model achieved spectral simulation accuracy comparable to PROSPECT-4 and was more suitable for parameter inversion of the physical and chemical properties of rice leaves, with relative root mean square errors of 7.4% for chlorophyll content, 5.6% for equivalent water thickness, and 7.5% for dry matter content. In conclusion, RSPECT improves radiative transfer modeling by integrating measurable anatomical features and provides a framework for extending this approach to other vegetation types.

hyperspectral↗
NASA NTRS2003

Sensitivity of Precipitation Processes to Microphysics and Resolution in a Cloud Resolving Model

The Goddard Cumulus Ensemble (GCE) model examines the impact of various microphysical schemes, and vertical and horizontal resolution in the development, intensity and rainfall associated with mesoscale convective systems, idealized hurricanes and an ensemble of clouds. The model variables include horizontal and vertical velocities, potential temperature, perturbation pressure, turbulent kinetic energy, and mixing rations of all water phases (vapor, liquid and ice). The major characteristics of the GCE model are the explicit representation of warm rain and ice microphysical processes, and their complex interactions with solar and infrared radiative transfer processes and with surface processes. For idealized hurricanes, an axisymmetric version of the GCE model was developed and used to simulate the tropical cyclogenesis process using both a Rankin vortex and saturated air within a specified radius as initial conditions. For mesoscale convective systems, the 3-D version of the GCE model was use to simulate squall lines that developed in the western Pacific, South China Sea, eastern Atlantic, South America and central U.S. FOr the cloud ensemble, the GCE model was integrated for several days in order to have a good sampling of cloud statistics. In this paper, the sensitivities of hurricane intensity to various microphysical processes and model grid resolutio will be examined. This will be mainly achieved by performing sensitivity tests using various horizontal (from 1-to 5-km) and vertical resolutions (from 20- to 200-m in the lower troposphere to 200- to 500m in the middle and upper troposphere). Sensitivity test using various microphysical schemes (warm rain only, and three ice with either graupel or hail) will also be performed. The thermodynamic and water budget associated with various types of precipitation systems will also be evaluated. The budgets will be calculated for different regions (i.e., convective and stratiform regions).

Tao, Wei-Kuo↗
DOE OSTI2019

Explore: An Advanced Computing Agenda for Competitiveness

Over the course of this three-year grant, the Council on Competitiveness (Council) hosted six meetings of its Advanced Computing Roundtable made up of experts from a broad cross section of advanced computing users and manufacturers, and four Advanced Computing for Competitiveness Regional Forums to explore issues related to advanced computing in regions, states and localities. More than two hundred experts, stakeholders and policymakers from the federal and state levels participated in this work and provided their time and expertise to help define the opportunity in advanced computing and the barriers to it reaching its full potential as a game-changing competitive advantage for the United States economy and national security. Building on the insights of the Council’s Advanced Computing Roundtable and findings and recommendations from the four U.S. Department of Energy-supported Forums, the Council has identified several broad policy objectives for the United States related to advanced computing leadership and implementation. The United States must: Compete at the high end of advanced computing. Continue investing to be a technology leader as the world moves toward exascale computing, including in hardware, software and applications. America also must lead in strategic areas like extending Moore’s Law and quantum computing. Improve the ability of HPC-using firms to leverage advanced computing. The Council recommends steps to improve computational skills, increase industry partnerships with laboratories and academia, and expand and strengthen software partnerships. Regulatory agencies also should accelerate efforts to use modeling and simulation within the regulatory process. Expand the number of HPC-using companies in America. Too few firms are able to leverage advanced computing to innovate and compete. Federal, state and local economic development efforts should be utilized to lower barriers and teach small and medium-sized firms, particularly manufacturers, to use advanced modeling, simulation and analytics. Coordinate federal action. Federal agencies should continue to act in a coordinated fashion on advanced computing challenges through the Joint Program Office for Strategic Computing. Leverage HPC to compete in strategic technologies and applications. Leadership in advanced computing is tightly linked to leadership in artificial intelligence, the Internet of Things, cybersecurity, additive manufacturing and other emerging technologies. Public and private sector leaders should collaborate on research and partnership efforts that ensure world-class computing environments for strategic technology leadership.

advanced computing↗
NASA NTRS2020

Marine wild-capture fisheries after nuclear war

Nuclear war, beyond its devastating direct impacts, is expected to cause global climatic perturbations through injections of soot into the upper atmosphere. Reduced temperature and sunlight could drive unprecedented reductions in agricultural production, endangering global food security. However, the effects of nuclear war on marine wild-capture fisheries, which significantly contribute to the global animal protein and micronutrient supply, remain unexplored. We simulate the climatic effects of six war scenarios on fish biomass and catch globally, using a state-of-the-art Earth system model and global process-based fisheries model. We also simulate how either rapidly increased fish demand (driven by food shortages) or decreased ability to fish (due to infrastructure disruptions), would affect global catches, and test the benefits of strong pre-war fisheries management. We find a decade-long negative climatic impact that intensifies with soot emissions, with global biomass and catch falling by up to 18 ± 3% and 29 ± 7% after a US-Russia war under business-as-usual fishing – similar in magnitude to the end-of-century declines under unmitigated global warming. When war occurs in an overfished state, increasing demand increases short-term (1-2 year) catch by at most ~30% followed by precipitous declines of up to ~70%, thus offsetting only a minor fraction of agricultural losses. However, effective pre-war management that rebuilds fish biomass could ensure a short-term catch buffer large enough to replace ~43 ± 35% of today’s global animal protein production. This buffering function in the event of a global food emergency adds to the many previously-known economic and ecological benefits of effective and precautionary fisheries management.

food from the ocean↗