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At least 1,567 records · Page 87

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DOE OSTI2025

Long-term hydro-economic analysis tool for evaluating global groundwater cost and supply: Superwell v1.1

Abstract. Groundwater plays a key role in meeting water demands, supplying over 40 % of irrigation water globally, with this role likely to grow as water demands and surface water variability increase. A better understanding of the future role of groundwater in meeting sectoral demands requires an integrated hydro-economic evaluation of its cost and availability. Yet substantial gaps remain in our knowledge and modeling capabilities related to groundwater availability, recharge, feasible locations for extraction, extractable volumes, and associated extraction costs, which are essential for large-scale analyses of integrated human–water system scenarios, particularly at the global scale. To address these needs, we developed Superwell, a physics-based groundwater extraction and cost accounting model that operates at sub-annual temporal and at the coarsest 0.5° (≈50 km × 50 km) gridded spatial resolution with global coverage. The model produces location-specific groundwater supply–cost curves that provide the levelized cost to access different quantities of available groundwater. The inputs to Superwell include recent high-resolution hydrogeologic datasets of permeability, porosity, aquifer thickness, depth to water table, recharge, and hydrogeological complexity zones. It also accounts for well capital and maintenance costs, as well as the energy costs required to lift water to the surface. The model employs a Theis-based scheme coupled with an amortization-based cost accounting formulation to simulate groundwater extraction and quantify the cost of groundwater pumping. The result is a spatiotemporally flexible, physically realistic, economics-based model that produces groundwater supply–cost curves. We show examples of these supply–cost curves and the insights that can be derived from them across a set of scenarios designed to explore model outcomes. The supply–cost curves produced by the model show that most (90 %) nonrenewable groundwater in storage globally is extractable at costs lower than USD 0.57 m−3, while half of the volume remains extractable at under USD 0.108 m−3. The global unit cost is estimated to range from a minimum of USD 0.004 m−3 to a maximum of USD 3.971 m−3. We also demonstrate and discuss examples of how these cost curves could be used by linking Superwell's outputs with other models to explore coupled human–environmental system challenges, such as water resources planning and management, or broader analyses of multisectoral feedbacks.

Global Change Analysis Model (GCAM)↗

DOE OSTI2017

Advanced Control of Next Generation Offshore Wind Turbines

Advanced turbine controls and structural dampers have the potential to significantly reduce the cost of energy (CoE) for offshore wind turbines. Progress made in these two areas on a Department of Energy (DoE) funded program is reported. A lidar-assisted control strategy, with objective to reduce component loads and increase energy capture, is developed and implemented. The controller has been tested in both simulations and on a 3MW utility-scale prototype. The controller results indicate a significant reduction in the tower fatigue loads. In a parallel effort, potential of a passive and semi-active tuned-mass damper (TMD) is evaluated to mitigate fatigue and extreme loads. Simulation results with passive and semi-active TMD indicate significant load reduction for tower and substructure for both fixed-bottom and floating wind turbines. Finally, levelized cost of energy modeling process to account for benefits of advanced controls is discussed.

structural dampers. cost of energy, lidar-assisted↗

NASA NTRS1979

Space shuttle solid rocket booster cost-per-flight analysis technique

A cost per flight computer model is described which considers: traffic model, component attrition, hardware useful life, turnaround time for refurbishment, manufacturing rates, learning curves on the time to perform tasks, cost improvement curves on quantity hardware buys, inflation, spares philosophy, long lead, hardware funding requirements, and other logistics and scheduling constraints. Additional uses of the model include assessing the cost per flight impact of changing major space shuttle program parameters and searching for opportunities to make cost effective management decisions.

Forney, J. A.↗

DOE OSTI2020

Cloud-based implementation of white-box model predictive control for a GEOTABS office building: A field test demonstration

Model predictive control (MPC) has been proven in simulations and pilot case studies to be a superior control strategy for large buildings. MPC can utilize the weather and occupancy schedule forecasts, together with the system model, to predict the future thermal behavior of the building and minimize the overall energy use and maximize thermal comfort. However, these advantages come with the cost of increased modeling effort, computational demands, communication infrastructure, and commissioning efforts. Thus a typical approach is to, often rapidly, simplify the building modeling and MPC optimization problem while paying a price of not reaching the full performance potential. It has been shown that by employing accurate physics-based models, MPC performance can be notably increased closer to its theoretical performance bound. However, implementation of such high-fidelity MPC in real buildings remains a challenge, resulting in a lack of successful field test studies. This work presents the methodology and field test demonstration of a computationally efficient implementation of the white-box MPC in an office building in Belgium. The detailed model of the building is based on first-principle physical equations. The deployment and supervision of MPC operation in a practical setting are supported by an automated cloud-based communication infrastructure. The motivating factor behind the cloud-based architecture is its compatibility with a commercially appealing control as a service concept. The building is equipped with a ground source heat pump (GSHP) and thermally activated building structures (TABS), where the combination of both is also known as GEOTABS. From a control perspective, GEOTABS buildings are particularly challenging systems due to large scale, complex heating, ventilation and air conditioning (HVAC) system, and slow dynamics with time delays. On the other hand, there is an increased potential for energy savings due to the high thermal mass, which acts as thermal storage. The MPC operation is demonstrated during the challenging transient seasons (switching between heating and cooling), and its performance is compared to a traditional rule-based controller (RBC). We provide a proof of concept of real MPC operation for the most difficult seasons with notable GSHP energy use savings equal to 53.5% and thermal comfort improvement by 36.9%. Other MPC applications found in the literature describe tests for only cooling or only heating, and up to now only for a black-box or a grey-box approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2017

A Measure-Theoretic Algorithm for Estimating Bottom Friction in a Coastal Inlet: Case Study of Bay St. Louis during Hurricane Gustav (2008)

The majority of structural damage and loss of life during a hurricane is due to storm surge, thus it is important for communities in hurricane-prone regions to understand their risk due to surge. Storm surge in particular is largely influenced by coastal features such as topography/bathymetry and bottom roughness. Bottom roughness determines how much resistance there is to the flow. Manning’s formula can be used to model the bottom stress with the Manning’s n coefficient, a spatially dependent field. Given a storm surge model and a set of model outputs, an inverse problem may be solved to determine probable Manning’s n fields to use for predictive simulations. The inverse problem is formulated and solved in a measure-theoretic framework using the state-of-the-art Advanced Circulation (ADCIRC) storm surge model. The use of measure theory requires minimal assumptions and involves the direct inversion of the physics-based map from model inputs to output data determined by the ADCIRC model. Thus, key geometric relationships in this map are preserved and exploited. By using a recently available subdomain implementation of ADCIRC that significantly reduces the computational cost of forward model solves, the authors demonstrate the method on a case study using data obtained from an ADCIRC hindcast study of Hurricane Gustav (2008) to quantify uncertainties in Manning’s n within Bay St. Louis. However, the methodology is general and could be applied to any inverse problem that involves a map from model input to output quantities of interest.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1972

Design of a space shuttle structural dynamics model

A 1/8 scale structural dynamics model of a parallel burn space shuttle has been designed. Basic objectives were to represent the significant low frequency structural dynamic characteristics while keeping the fabrication costs low. The model was derived from the proposed Grumman Design 619 space shuttle. The design includes an orbiter, two solid rocket motors (SRM) and an external tank (ET). The ET consists of a monocoque LO2 tank an interbank skirt with three frames to accept SRM attachment members, an LH2 tank with 10 frames of which 3 provide for orbiter attachment members, and an aft skirt with on frame to provide for aft SRM attachment members. The frames designed for the SRM attachments are fitted with transverse struts to take symmetric loads.

Source record↗

DOE OSTI2016

Quantifying the Impact of Feedstock Quality on the Design of Bioenergy Supply Chain Networks

Logging residues, which refer to the unused portions of trees cut during logging, are important sources of biomass for the emerging biofuel industry and are critical feedstocks for the first-type biofuel facilities (e.g., corn-ethanol facilities). Logging residues are under-utilized sources of biomass for energetic purposes. To support the scaling-up of the bioenergy industry, it is essential to design cost-effective biofuel supply chains that not only minimize costs, but also consider the biomass quality characteristics. The biomass quality is heavily dependent upon the moisture and the ash contents. Ignoring the biomass quality characteristics and its intrinsic costs may yield substantial economic losses that will only be discovered after operations at a biorefinery have begun. Here this paper proposes a novel bioenergy supply chain network design model that minimizes operational costs and includes the biomass quality-related costs. The proposed model is unique in the sense that it supports decisions where quality is not unrealistically assumed to be perfect. The effectiveness of the proposed methodology is proven by assessing a case study in the state of Tennessee, USA. The results demonstrate that the ash and moisture contents of logging residues affect the performance of the supply chain (in monetary terms). Higher-than-target moisture and ash contents incur in additional quality-related costs. The quality-related costs in the optimal solution (with final ash content of 1% and final moisture of 50%) account for 27% of overall supply chain cost. In conclusion, based on the numeral experimentation, the total supply chain cost increased 7%, on average, for each additional percent in the final ash content.

09 BIOMASS FUELS↗

DOE OSTI2018

Strategic Offering for Wind Power Producers Considering Energy and Flexible Ramping Products

The increasing deployments of renewable generation methods, such as wind, affects the flexibility of electric power system operating due to their inherent variability and uncertainty. To mitigate this, power systems need flexible resources. This paper investigates the potential for wind power to provide flexible ramping products in the real-time market, an additional value stream to the energy it provides. The proposed model for wind power’s strategic offering is formulated as a bi-level optimization problem with wind profit maximization at the upper level and the independent system operator’s economic dispatch—considering both the energy balance and the flexible ramping requirement to counter uncertainty—at the lower level. This bi-level model is converted to a mathematical program with equilibrium constraints (MPEC) by recasting the lower level problem with its Karush–Kuhn–Tucker optimality conditions. Then, through strong duality theory and the big-M method, the MPEC model is converted to a mixed-integer linear programming model. The opportunity cost and the price for wind power-providing ramping products are analyzed. Numerical examples based on a 5-bus network are presented to verify the proposed model and concept.

17 WIND ENERGY↗

DOE OSTI2021

The Value of Increased HVDC Capacity Between Eastern and Western U.S. Grids: The Interconnections Seam Study

The Interconnections Seam Study examines the potential economic value of increasing electricity transfer between the Eastern and Western Interconnections using high-voltage direct-current (HVDC) transmission and cost-optimizing both generation and transmission resources across the United States, proposing, assessing, justifying, and illustrating a major infrastructure change involving two of the worlds largest power grids. The study conducted a multi-model analysis that used co-optimized generation and transmission expansion planning and production cost modeling. Four transmission designs under eight scenarios were developed and studied to estimate costs and potential benefits. The results show benefit-to-cost ratios that reach as high as 2.5, indicating significant value to increasing the transmission capacity between the interconnections under the cases considered, realized through sharing generation resources and flexibility across regions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

A cost comparison of various hourly-reliable and net-zero hydrogen production pathways in the United States

Hydrogen (H 2 ) as an energy carrier may play a role in various hard-to-abate subsectors, but to maximize emission reductions, supplied hydrogen must be reliable, low-emission, and low-cost. Here, we build a model that enables direct comparison of the cost of producing net-zero, hourly-reliable hydrogen from various pathways. To reach net-zero targets, we assume upstream and residual facility emissions are mitigated using negative emission technologies. For the United States (California, Texas, and New York), model results indicate next-decade hybrid electricity-based solutions are lower cost ($2.02-$2.88/kg) than fossil-based pathways with natural gas leakage greater than 4% ($2.73-$5.94/kg). These results also apply to regions outside of the U.S. with a similar climate and electric grid. However, when omitting the net-zero emission constraint and considering the U.S. regulatory environment, electricity-based production only achieves cost-competitiveness with fossil-based pathways if embodied emissions of electricity inputs are not counted under U.S. Tax Code Section 45V guidance.

08 HYDROGEN↗

DOE OSTI2018

U.S. energy sector impacts of technology innovation, fuel price, and electric sector CO2 policy: Results from the EMF 32 model intercomparison study

We study the impact of fuel prices, technology innovation, and a CO2 emissions reduction policy on both the electric power and end-use sectors by comparing outputs from four U.S. energy-economic models through the year 2050. Achieving innovation goals decreases CO2 emissions in all models, regardless of natural gas price, due to increased energy efficiency and low-carbon generation becoming more cost competitive. For the models that include domestic natural gas markets, achieving innovation goals lowers wholesale electricity prices, but this effect diminishes as projected natural gas prices increase. Higher natural gas prices lead to higher wholesale electricity prices but fewer coal capacity retirements. A CO2 electric power sector emissions cap influences electric sector evolution under reference technology assumptions but has little to no incremental influence when added to innovation goals. Long-term, meeting innovation goals achieves a generation mix with similar CO2 emissions compared to the CO2 policy but with smaller increases to wholesale electricity prices. In the short-term, the relative effect on wholesale prices differs by model. Finally, higher natural gas prices, achieving innovation goals, and the combination of the two, increases the amount of renewable generation that is cost-effective to build and operate while slowing the growth of natural-gas fired generation, which is the predominant generation type in 2050 under reference conditions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Accurate and efficient interatomic potentials are essential for molecular dynamics (MD) simulations of radiation damage, gas diffusion, and phase stability in complex ceramics such as LiAlO 2 , especially under extreme conditions relevant to tritium production. Here, we evaluate the performance of six machine-learned interatomic potentials (MLIPs), moment tensor potential (MTP), Gaussian approximation potential, deep potential (DeePMD), atomic cluster expansion (ACE), message-passing ACE (multilayer atomic cluster expansion (MACE) pretrained) and MACE (trained from-scratch), all trained on the same density functional theory dataset with inclusion of tritium. The MLIPs are benchmarked against traditional Buckingham and ReaxFF potentials in terms of energy accuracy, density predictions, thermal equilibration behavior, threshold displacement energy (E d ), tritium diffusivity, and computational cost. Among the models, MTP shows the best overall balance between efficiency and accuracy, with low force and energy errors and realistic E d values for Li and Al. The ACE and MACE (pretrained and trained from scratch) models exhibit high E d (>200 eV) and unphysical pair interactions. DeePMD underestimates Ed due to overly repulsive behavior even at equilibrium distances. All models over-estimate tritium diffusion but the pretrained MACE model behaves well during tritium-diffusion simulations up to 500 K, maintaining diffusivities in the physically consistent 10 −11 m 2 /s range. Finally, we quantify the computational cost of each potential in large-scale atomic/molecular massively parallel simulator, finding that only MTP is more efficient than traditional empirical potentials, while others are significantly more expensive. These findings explain the trade-offs between accuracy and computational cost in MLIP development and provide essential guidance for use in high-throughput radiation damage and gas diffusion simulations in nuclear ceramics.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2017

Steam Accumulator Storage Integration into a Nuclear Power Plant

The growth of non-dispatchable renewables benefits technologies with flexible load capabilities. Baseload technologies must accept low prices and revenues during low-demand periods that arise with increasing frequency as renewables deployment grows. For this reason, generators such as combined cycle gas turbines threaten to out-compete baseload, and nuclear power plants are facing early retirement. If utilities are to consider future nuclear power plants to be attractive investments they must excel at roles other than baseload generation. Energy storage offers a means to avoid times of low prices and capitalize on times of high prices, as well as for nuclear to participate in ancillary markets and provide grid stability and regulation services. This paper explores the use of steam accumulators to store energy for a pressurized water reactor (PWR). The discharging steam from the accumulator provides heat to a feedwater heater, replacing steam, which bleeds off of the high-pressure turbine during normal operation. The utilization of the accumulator as a heat source for the feedwater heater increases the electrical power output of the PWR during discharge, as more electricity can be produced for a constant thermal input from the steam generator. This study first presents the proposed layout of the steam accumulator integrated into a PWR and the base case values used. Next a brief overview of the thermodynamic model governing the charging and discharging processes of the accumulator is presented. An economic model describes the capital cost estimation and revenue potential for the system. These models are evaluated at varying values of energy, power, and pipe lengths. Results show the relationship between energy, power, and accumulator size, and their effect on net annual revenue and storage efficiency. The cases presented here provide direction for future work for optimizing the size and power output of the accumulator.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Mining Air for Fuels and Fine Chemicals

The Intergovernmental Panel on Climate Change’s 2021 report underscores that Direct Air Capture (DAC) is an essential component to limiting global warming to 2 °C, yet separating CO 2 from air and its subsequent concentration for conversion into carbon neutral fuels/chemicals or permanent storage remains energy intensive and costly. Further, most DAC technologies rely on repetitive capture and release cycles that reduces the amount of time the DAC materials are able to collect CO 2 and increases wear and tear. Moisture swing (MS) sorption within anion exchange materials utilizes differences in relative humidity to capture and concentrate CO 2 up to 500-fold with negligible energy inputs and low-cost sorbents. Molecular modeling predicts that membranes with a dry and wet side would actively transport CO 2 from its dry side to its wet side against a counter flow of H 2 O evaporating on the dry side, however, existing MS materials are too brittle to be processed into membranes to test this hypothesis. This project brought together experts in DAC materials and design, techno-economic analysis and project management at Arizona State University (ASU), polymer processing at University of Texas at Austin (UTA) and modeling gas transport and exchange at Norther Arizona University (NAU) to develop hollow fiber membranes that use energy from water evaporation to continuously pump CO 2 from air against a concentration gradient to the membranes interior and requiring significantly less energy than current DAC technologies. While this project did not meet its ultimate objectives of demonstrating an active CO 2 pumping membrane, a number of key accomplishments were made in developing low-cost, flexible anion exchange membranes (AEM) at 3.5 m 2 scale, characterizing the ionic and molecular transport within MS materials, and developing several analytical and mathematical models of the MS and pumping process leading to new fundamental knowledge about key rate limiting steps of CO 2 flux in anion exchange membranes at low water activity. Technoeconomic models show that if CO 2 fluxes ≥ 25 µmol CO 2 m -2 s -1 (membrane surface area) are achieved that cost ≤ $\$$100/tonne CO 2 captured, purified and compressed to pipeline quality is possible. The knowledge gained in this research will guide future research in developing new materials toward overcoming these rate limiting steps that in turn could enable transformative and disruptive DAC technologies needed for capturing gigatons of CO 2 per year needed to limiting global warming to 2 °C.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Data for Post-Access Report: Tidal Energy Resource Characterization and Model Validation via the Assessment of Cost-effective Spatially Distributed Current Measurements from microFloat Swarms

This project evaluated how high-resolution, spatially distributed field data can be used to refine and validate site-scale hydrodynamic simulations of tidal channels. Use of such spatially-distributed field observations or site-scale hydrodynamic simulations will be needed for producing accurate predictions of tidal energy production over larger arrays of tidal turbines. The data contained in this archive includes field observations of water velocity from a series of short surveys in Agate Pass taken on August 20th, 2020 using station-keeping ADCP (acoustic doppler current profiler) measurements, drifting downward-looking ADCPs, and microFloats, gathered by researchers at APL-UW under a previous project. It also includes high-resolution hydrodynamic model runs for the site during that time generated under TEAMER support. An explanatory file (.pdf format) describes the survey and field data structure. Processed data is stored in .mat format. Survey summary: start time, number of floats, water level. microFloat data: - Cleaned data for each float in survey, - Time series of position (lat., lon.), depth (relative to surface), and horizontal velocity (u, v) Drifting ADCP data: - Cleaned data for each drifting ADCP in survey - Time series of position (lat., lon.), sample depth (relative to surface), and observed water velocity (u,v,w) Stationary ADCP data: - Cleaned data for each station-keeping data set in survey - Time series of position (lat., lon.), sample depth (relative to surface), and observed water velocity (u,v,w) FVCOM (Finite Volume Coastal Ocean Model) model outputs: Water level and velocity, as well as derived variables (e.g., power density) from the final refined model simulations for the Agate Pass subdomain. Contained in NetCDF and ASCII files for the duration of August 18th and 20th 2020 field surveys. Additional scripts for processing the data and generating the figures in the report are included.

16 TIDAL AND WAVE POWER↗

DOE OSTI2020

Assessing Uncertainties and Approximations in Solar Heating of the Climate System

In calculating solar radiation, climate models make many simplifications, in part to reduce computational cost and enable climate modeling, and in part from lack of understanding of critical atmospheric information. Whether known errors or unknown errors, the community's concern is how these could impact the modeled climate. The simplifications are well known and most have published studies evaluating them, but with individual studies it is difficult to compare. Here, we collect a wide range of such simplifications in either radiative transfer modeling or atmospheric conditions and assess potential errors within a consistent framework on climate-relevant scales. We build benchmarking capability around a solar heating code (Solar-J) that doubles as a photolysis code for chemistry and can be readily adapted to consider other errors and uncertainties. The broad classes here include: use of broad wavelength bands to integrate over spectral features; scattering approximations that alter phase function and optical depths for clouds and gases; uncertainty in ice-cloud optics; treatment of fractional cloud cover including overlap; and variability of ocean surface albedo. We geographically map the errors in W m -2 using a full climate re-creation for January 2015 from a weather forecasting model. For many approximations assessed here, mean errors are ~2 W m -2 with greater latitudinal biases and are likely to affect a model’s ability to match the current climate state. Combining this work with previous studies, we make priority recommendations for fixing these simplifications based on both the magnitude of error and the ease or computational cost of the fix.

58 GEOSCIENCES↗

DOE OSTI2019

CSP Systems Analysis - Final Project Report

The CSP Systems Analysis project was a three-year effort supporting the Concentrating Solar Power (CSP) Subprogram within the Solar Energy Technologies Office of the U.S. Department of Energy (DOE). The goal of the CSP Systems Analysis project was to provide timely and accurate CSP cost data to the DOE and predict performance and cost for emerging technologies that may impact research directions and industry investment. The project consisted of six, mostly independent tasks. Major accomplishments over the three-year period of performance were as follows. The NREL team maintained current cost estimates for CSP technologies by annual updates to the cost input parameters within NREL's System Advisor Model (SAM). SAM is a performance and cost simulation software that includes technology models for the primary CSP technologies. During the period from 2016 to 2018, the estimated cost within SAM's default CSP molten-salt power tower technology dropped from 13.0 to 11.1 cent/kWh (real dollars without incentives). Power cycle models for the supercritical carbon dioxide (sCO2) Brayton Cycle were developed and made an option within SAM's molten-salt power tower model. These models were subsequently used to evaluate the cost reduction potential of alternative salts. The partial-cooling model was found to provide the greatest cost-reduction potential due to its combination of efficiency and temperature differential across the turbine and thermal energy storage (TES) system. These studies were documented in two journal articles. NREL's optical modeling software SolTrace and SolarPILOT were made more versatile and released as open-source software to the CSP community. These tools help researchers and developers to model and optimize the optical performance of CSP collector systems. The new features were highlighted in a recorded webinar that can be accessed from the NREL SAM website. New models for solar-thermal systems, that is, applications for solar industrial process heat, were developed, validated, and installed within SAM. The analysis includes a 2018 review of linear collectors in the market that are tailored for solar process heat applications. In 2018 the NREL team also developed an annual simulation for a direct steam generation system integrated with a latent-heat TES system. This analysis was submitted for journal publication. The NREL team continued to support the exchange of information and development of CSP guidelines within the international CSP community of SolarPACES. Much of the work under this project was presented at SolarPACES, including the development of a modeling checklist to help CSP stakeholders standardize the models used for estimating CSP performance and cost. The CSP Systems Analysis project also supported DOE requests for tracking and reporting programmatic targets for the CSP Subprogram.

14 SOLAR ENERGY↗

NASA NTRS2009

Benefits to the Simulation Training Community of a New ANSI Standard for the Exchange of Aero Simulation Models

The American Institute of Aeronautics Astronautics (AIAA) Modeling and Simulation Technical Committee is in final preparation of a new standard for the exchange of flight dynamics models. The standard will become an ANSI standard and is under consideration for submission to ISO for acceptance by the international community. The standard has some a spects that should provide benefits to the simulation training community. Use of the new standard by the training simulation community will reduce development, maintenance and technical refresh investment on each device. Furthermore, it will significantly lower the cost of performing model updates to improve fidelity or expand the envelope of the training device. Higher flight fidelity should result in better transfer of training, a direct benefit to the pilots under instruction. Costs of adopting the standard are minimal and should be paid back within the cost of the first use for that training device. The standard achie ves these advantages by making it easier to update the aerodynamic model. It provides a standard format for the model in a custom eXtensible Markup Language (XML) grammar, the Dynamic Aerospace Vehicle Exchange Markup Language (DAVE-ML). It employs an existing XML grammar, MathML, to describe the aerodynamic model in an input data file, eliminating the requirement for actual software compilation. The major components of the aero model become simply an input data file, and updates are simply new XML input files. It includes naming and axis system conventions to further simplify the exchange of information.

Hildreth, Bruce L.↗