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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 19 records

Multi-scale, Multi-disciplinary, and Multi-agent Explainable AI with Koopman-Undergirded Learning, Prediction, and Analysis (M3EA KULPA) (Project Closeout Report)

The goal of this project was to develop and use domain-aware machine learning formulations, based on the Koopman Operator (KO), for modelling multi-scale, multi-disciplinary (e.g., multi-physics), and/or multi-agent systems. The project developed these formulations for the following cases: • Systems with dynamics at two separate time scales, • Systems with a bi-level hierarchical control structure, • Systems with bi-level hierarchical control and dynamics at two separate time scales (the lower level controls operating at the faster time scale), and • Systems with n separate but interacting agents/disciplines (with/without control, respectively); the controls for each agent could include bi-level hierarchical control and dynamics at two separate time scales as described above. The project then defined a set of dynamical systems consisting of different nonlinear oscillators that could be used to test these different formulations and then subsequently learned the KO models for those systems. With the KO models, we were able to do the following: • Quantify system stability, including both long-term and transient behavior, • Quantify the effects of feedbacks between the different time scales and agents/disciplines in terms of those feedbacks’ effects on system stability, • Replace a standard Proportional-Integral (PI) control in the hierarchical control structure with a KO-based Linear-Quadratic Regular (LQR), a form of optimal control, • Calculate optimal supervisory control policies a) with and without time scale separated dynamics at the lower level control levels and b) with both PI and KO-based LQR lower level control policies, and • Calculate dynamic Nash equilibria for multi-agent systems where each agent makes its own control decisions.

97 MATHEMATICS AND COMPUTING↗

Manganese in drinking-water reservoirs: a multi-disciplinary review of current issues, biogeochemical controls, and oxygenation-based management

Decreased water quality and increased treatment costs due to excess manganese (Mn) in drinking-water supplies are critical issues globally. To combat on-going and emerging taste and odour issues with Mn and other contaminants (e.g., algal toxins), many utilities are using engineered oxygenation or aeration (EOA) systems to improve water quality in lakes and reservoirs. Resultant shifts in key biogeochemical and physical processes are still poorly understood, often leading to inefficiently managed systems. Paired with knowledge gaps regarding environmental drivers of Mn and the complexity of Mn redox kinetics, Mn problems persist. This review presents the state of current research in areas critical to optimisation of EOA mitigation of Mn, with focus on i) Mn biogeochemical cycling within drinking-water reservoirs; ii) influences of local catchment geology, hydrology, and land use on Mn dynamics; and iii) Mn management using different EOA approaches. The importance of considering the combined implications of these factors for successful Mn management in reservoirs is highlighted by an evaluation of relevant field-based studies; a wide range in EOA performance is observed, from a 97 % decrease in soluble Mn up to a ∼400 % increase in total Mn. Despite the breadth of studies that consider Mn in water-supply systems, there are still several areas of research which warrant further investigation, including: the influence of natural sources and anthropogenic activities on Mn within a given catchment, Mn speciation and transport in stratified and destratified lakes and reservoirs, and optimal site-specific EOA strategies for Mn mitigation.

Aeration↗

Development of a multi-disciplinary ERTS user program in the state of Ohio

The author has identified the following significant results. A preliminary comparison of the land use maps derived from high altitude photography and imagery generated from land use CCT's shows considerable correlation of data. Most land use features are best identified on LANDSAT data taken over a full year, showing the effects of the four seasons. It appears that the most cost effective and timely way of providing land use data is to use LANDSAT data for identifying 75 to 90 percent of land use categories, using temporal data. For surface mining, close examination of LANDSAT, Skylab, and aircraft data covering the same area where linears were found seems to indicate that the type of resolution characteristic of LANDSAT data results in a better definition of linears of one or more miles. Long line linears were found in the vicinity of known gas production areas in Ohio.

Baldridge, P. E.↗

Development of a multi-disciplinary ERTS user program in the state of Ohio

The author has identified the following significant results. Although the analysis of the results of presently - used methodology has showed inadequate correlation between the land use change and the various socio-economic factors, a system of analysis was produced that will aid in the future work in this area pointing out the adequacy of the land use data for producing models of desired accuracy. This testing methodology is applicable to other LANDSAT/land use interpretation systems.

Baldridge, P. E.↗

Development of a multi-disciplinary ERTS user program in the state of Ohio

The author has identified the following significant results. The State of Ohio has an inventory in machine compatible form, such that, information about the land use in Ohio may be tailored to the requirements of the user and may be easily modified and updated as future needs arise.

Baldridge, P. E.↗

Development of a multi-disciplinary ERTS user program in the state of Ohio. Volume 1: Executive summary

The author has identified the following significant results. A current uniform land inventory was derived, in part, from LANDSAT data. The State has the ability to convert processed land information from LANDSAT to Ohio Capability Analysis Program (OCAP). The OCAP is a computer information and mapping system comprised of various programs used to digitally store, analyze, and display land capability information. More accurate processing of LANDSAT data could lead to reasonably accurate, useful land allocations models. It was feasible to use LANDSAT data to investigate minerals, pollution, land use, and resource inventory.

Baldridge, P. E.↗

A multi-disciplinary approach to structural design for stochastic loads

The development of aircraft gust design techniques is reviewed with emphasis on those techniques applicable to large scale multidisciplinary closed-loop optimization methods. An overall view is presented of the optimization methodology utilized. An analysis is presented wherein the bivariate normal distribution function for a particular loading condition is considered. By use of maximization techniques, functions are derived for stress components along equal probability contours which allow for directionality and auto-correlation effects to be considered. These functions are then applied to the problem being considered and the effects on the structural sizing and weight penalties evaluated against more conventional methods.

Gross, D. W.↗

Ard [SWR-25-18]

A wind farm optimization suite for wind energy that is built for modular, gradient-enabled multi-disciplinary and multi-fidelity optimizations. Dig into wind farm design. An ard is a type of simple and lightweight plow, used through the single-digit centuries to prepare a farm for planting. The intent of Ard is to be a modular, full-stack multi-disciplinary optimization tool for wind farms. The problem with wind farms is that they are complicated, multi-disciplinary objects. They are aerodynamic machines, with complicated control systems, power electronic devices, social and political objects, and the core value (and cost) of complicated financial instruments. Moreover, the design of one of these aspects affects all the rest! Ard seeks to make plant-level design choices that can incorporate these different aspects and their interactions to make wind energy projects more successful.

Frontin, Cory [National Renewable Energy Laborator↗

Multidisciplinary Design, Analysis, and Optimization (MDO) for Co-Designed Transmission & Distribution Electric Grid Planning

This paper describes early experiences and example use cases applying multi-disciplinary design analysis and optimization (MDO) to the integrated design of power grids. Adapted from aerospace, MDO enables combining multiple existing tools into a coordinated optimization. Here we use MDO to simultaneously capture integrated transmission-distribution and investment-engineering trade-offs in an automated framework. Example use cases showcase prototype interactions among existing grid models using MDO and hint at the types of integrated analyses enabled by this approach. In addition, we share experiences and thoughts on grid-specific challenges and opportunities to help advance further work in this area.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Developing a digital twin framework for remotely monitoring nuclear reactor facilities

A digital twin must seek to represent all applicable functional components of the system of interest. Different expertise is required for understanding the physical system being modeled than the skills needed for transforming those models into a functional digital twin through physics modeling, machine learning analysis, and visualization. The diversity of knowledge requires a multi-disciplinary team to ensure all system details are captured. Team members also need a method to verify that the data they generate within their domain can be effectively communicated to professionals in other fields. To address this challenge, this work provides an approach for developing a digital twin framework to remotely monitoring nuclear facilities. Through this, general knowledge of the framework is presented along with two examples to solidify the process. The AGN-201 digital twin and microreactor digital twins provide varying levels of complexity in a potential nuclear facility, where common threads are identified and lessons learned are provided. The goal of this research is to aid future researchers by providing a formula for a successful digital twin and in turn reducing the development time of nuclear system digital twins, specifically for remote monitoring.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Primary System Thermal Fluids Analysis Model Development for the Compact High Temperature Gas Reactor (HC-HTGR) (Final Report)

Horizontal Compact High Temperature Gas Reactor (HC-HTGR) is being designed by a multi-disciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed HC-HTGR and support its commercialization as a safe, low-cost HTGR. Argonne National Laboratory (Argonne) is collaborating on the thermal hydraulic design and analysis of HC-HTGR reactor pressure vessel internals to ensure the reactor maintains sufficient safety margins during normal operation, shutdown, and accident conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Cell to Ecosystem: Understanding Methane and Associated Nutrient Cycling by Sediment Hosted Syntrophic Consortia and Their Viral Predators

The anaerobic oxidation of methane (AOM) is a significant worldwide microbial process in anoxic lake and ocean sediments, responsible for sequestering up to 80% of this greenhouse gas. Often considered a metabolism on the edge of thermodynamic probability, the impact of ANaerobic MEthane-oxidizing ‘ANME’ archaea on carbon and nutrient cycling in sediment ecosystems is far reaching. They not only serve as a sink for methane coupled to diverse electron acceptors, but also catalyze the transformation of many important nutrients including nitrogen, phosphate, and iron. While information about the potential mechanisms supporting metabolism in AOM is now available, remarkably little has been learned about their nutritional requirements, their dependencies on bacterial partners, and consequentially their ultimate impact on nutrient transformation and bioavailability within sedimentary ecosystems, and beyond. Further, the role of viruses within sediment ecosystems represents an essential but vastly understudied aspect of the transformation of carbon and nutrients by AOM. Viruses are now widely appreciated as central players in biogeochemical cycles across diverse ecosystems. These nanoscale predators have been shown to enhance the turnover of essential nutrients, thus stimulating microbial growth and environmental viruses themselves may constitute an important reservoir of nitrogen and phosphorous. Little is known about the role of viruses in methane-impacted sedimentary ecosystems, however prior genomic and microscopy evidence suggests that AOM consortia are susceptible to phage infection. The overarching scientific goal of this multi-disciplinary research proposal is to build on these recent discoveries and expand our understanding of interactions and fundamental activities involved in cycling of carbon and nutrients by syntrophic methanotrophic archaeal-bacterial consortia and associated viruses in anoxic sedimentary environments. Our three specific objectives are to 1) Quantify energy and nutrient exchange (e.g. N, P, Fe and vitamins) within AOM consortia and between ANME-bacterial partners; 2) Identify virus-host interactions associated with AOM and assess C and N transfer through viruses in methane-impacted sediment ecosystems; 3) Model energy and nutrient exchange in AOM consortia and viral-host interactions (i.e. viral activity), and their environmental distribution patterns. Our experimental emphasis cuts across scales that are important for understanding microbial and viral interactions and activities within their habitats, as well as community wide biogeochemical transformations. These research goals will be accomplished through the application of novel molecular techniques targeting DNA, RNA, proteins, and metabolites combined with a unique multi-modal analytical imaging pipeline. We will then model the ecophysiological capabilities of diverse sediment-hosted methanotrophic consortia to develop a more comprehensive understanding of the energetic and nutritional interactions between different AOM partner couplings that occur in sediments.

03 NATURAL GAS↗

LDRD 2024 Annual Report: Laboratory Directed Research and Development Program Activities

One fundamental question underlying all living organisms is the need to understand their hierarchical organizations and physical changes with the necessary spatial and temporal resolutions under physiological or pathological conditions. This is a multi-scale challenge requiring imaging from sub-nanometers to micrometers in a cellular context. While individual imaging techniques are available, there is a critical need to integrate them into a workflow capability. Our objective is to develop an integrated multi-disciplinary and multi-scale bioimaging capability at Brookhaven National Laboratory (BNL). The capability expands BNL’s existing facility operation program in bioimaging and positions BNL in a leadership position in bioimaging research. The capability also addresses the grand challenges of the Department of Energy (DOE) science programs for national bioenergy sustainability and security.

99 GENERAL AND MISCELLANEOUS↗