Powernet A tech platform to optimize agriculture management and operations
Food production needs to grow rapidly! Advances in food production have been focused in specific silos...electricity, environment, and water.
60 APPLIED LIFE SCIENCES↗
SEARCH · Engineering Papers
Results for “Advanced Optimization”
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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Space programs summary no. 37-26, volume IV FOR the period February 1, 1964 to March 31, 1964. Supporting research and advanced development
Research project summaries in propulsion, guidance and control, trajectory optimization, physics and chemistry, communications, and related space sciences
TRAJECTORY OPTIMIZATION↗
Evaluation of advanced superalloy protection systems
Electron beam vapor deposited CoCrAlY coating composition optimization with ballistic impact and furnace/long term burner rig oxidation tests
Elam, R. C.↗
Single step optimization strategies for constrained retargeting maneuvers
The present consideration of recent advancements in the nonlinear guidance of spacecraft, using feedback linearization and decoupling to generate exact nominal commands, gives attention to the correction of saturation effects and oscillation prevention in saturated operating regimes. In the case of spacecraft maneuvered by momentum-transfer devices, real time command generation is possible by means of pointwise minimization of the sum of the squares of the norms of the 'next state error' for the equivalent system and the linear system input. It is also possible to track a nominal trajectory, such as a critically damped harmonic oscillator response, by minimizing the square of the norm of the error between the actual and the tracked states.
Dwyer, T. A. W., III↗
Some Approaches Towards Constructing Optimally Efficient Multigrid Solvers for the Inviscid Flow Equations
Some important advances took place during the last several years in the development of genuinely multidimensional upwind schemes for the compressible Euler equations. In particular, a robust, high-resolution genuinely multidimensional scheme which can be used for any of the flow regimes computations was constructed. This paper summarizes briefly these developments and outlines the fundamental advantages of this approach.
Sidilkover, David↗
Optimized Heat Pipe Backup Cooling System Tested with a Stirling Convertor
Advanced Stirling Radioisotope Generator (ASRG) is an attractive energy system for select space missions, and with the addition of a VCHP, it becomes even more versatile. The ASRG is powered through thermal energy from decaying radioisotopes acting as General Purpose Heat Sources (GPHS). A Stirling engine converts the thermal energy to electrical energy and cools the GPHS [2]. The Stirling convertor must operate continuously to maintain acceptable temperatures of the GPHS and protect their cladding. The addition of alkali metal VCHP allows the Stirling to cycle on and off during a mission and can be used as a backup cooling system. The benefits of being able to turn the Stirling off are: allowing for a restart of the Stirling and reducing vibrations for sensitive measurements. The VCHP addition should also increase the efficiency of the Stirling by providing a uniform temperature distribution at the heat transfer interface into the heater head.
Stirling Radioisotope Generator↗
Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs
The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.
Artificial Intelligence (AI)↗
Advanced Materials and Additive Manufacturing for Phase Change Thermal Energy Storage and Management: A Review
Abstract Phase change materials (PCMs) can enhance the performance of energy systems by time shifting or reducing peak thermal loads. The effectiveness of a PCM is defined by its energy and power density—the total available storage capacity (kWh m −3 ) and how fast it can be accessed (kW m −3 ). These are influenced by both material properties as well as geometry of the energy systems; however, prior efforts have primarily focused on improving material properties, namely, maximizing latent heat of fusion and increasing thermal conductivity. The latter is often at the expense of the former. Advanced manufacturing techniques hold tremendous potential to enable co‐optimization of material properties and device geometry, while potentially reducing material waste and manufacturing time. There is an emerging body of research focused on additive manufacturing of PCM composites and devices for thermal energy storage (TES) and thermal management. In this article, the fundamentals and applications of PCMs are reviewed and recent additive manufacturing advances in latent heat TES for both the PCM composite and associated heat exchanger are discussed. A forward‐looking perspective on the future and potential of PCM additive manufacturing for TES and thermal management is provided.
25 ENERGY STORAGE↗
Summary of Technical Interchange Meetings (TIMs) Designed to Enable Earth Independent Medical Operations (EIMO)
The Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program hosted a series of TIMs in 2023-2024 designed to stimulate discussion around specific topics with the goal of enabling EIMO. In context of the thematic constituent elements of EIMO, namely pre-mission planning, acute/emergent/prolonged medical decision making, supply/resource management and task load management, subject matter experts from industry, academia and government (NASA and other Agencies) provided valuable and actionable guidance and recommendations. Earth-based medical experts will remain indispensable for pre-mission planning, however, management of acute/emergent medical contingencies will require a gradual transition of medical care and decision making from terrestrial to space-based assets to enable support of astronaut health and performance and reduce overall mission risk. Key to achieving these enhancements is providing an integrated data system platform capable of utilizing multiple data streams in concert with a variety of on-board databases and passive monitoring of video and wearable sensors to enable a multi-modal, agentic AI-based clinical decision support system (CDSS) to support crew medical officer (CMO) medical decision-making. The EIMO series of TIMs (I-V) have proven to be instructive and portend a significant paradigm shift will be necessary to maintain crew health and performance on exploration class missions. Importantly, since the expected paradigm shift will be significantly different from the methods of operation that have been employed for the majority of missions from the inception of human spaceflight to date, any proposed methods must be deployed in the setting of ongoing operations early and be “tested, reviewed and practiced” while reliable back-up is available to facilitate an Enterprise-wide level of comfort and acceptance. Serious constraints on data transmission coupled with a large and expanding universe of on-board medical informatics data streams will necessitate implementation of a CDSS to supplant the current reliance on support provided by ground-based SMEs. Establishment of trust in the system by CMO/crew and the ground-based medical support team will be essential. Co-development of a CDSS with industry partners will assure that state of the art tools can be employed, and industry efficiencies can be leveraged. Training regimens, materials and tools must evolve to be responsive (just-in-time training) and facilitate autonomous execution of procedures. Proficiency metrics should be established and be based on validated competencies or milestones as opposed to a prescribed number of training hours. Training should be prioritized for broad, translatable skills that have universal application across a variety of medical conditions. Repetition was deemed to be the key to achieving proficiency and emphasis should lie in procedural training which is known to extinguish more rapidly than diagnostic skills. Advanced tools, e.g., extended reality, can provide more realistic and effective training. Use of advanced probabilistic risk assessment tools will be essential to optimize the medical system capability while carefully balancing risk relative to mass/power/volume limitations. Importance of factoring use-life of medical supplies and maintaining awareness of redundancy and opportunity to re-purpose under off nominal situations was emphasized. Consideration of adopting optimized performance standards vs. “good-enough” performance thresholds is warranted. The use of legacy systems as opposed to creating new systems may be preferable. Managing task load and associated cognitive load will be essential to maintain operational safety and behavioral health. ExMC aspires to create a shared EIMO paradigm and strategic vision for advancing medical system design through novel technologies, training, protocols, and support capabilities, built upon the spirit of successful strategies and innovations over the past six decades of space medicine operations.
Jay Lemery↗
Differences In High Burnup Fuel Management Strategies to Minimize FFRD and Increase Economic Viability
The nuclear industry is pursuing approval of an increase in the length of the pressurized water reactor (PWR) cycle from 18 months to 24 months to reduce reactor downtime and enhance the economic competitiveness of nuclear energy. Such an increase in reactor cycle length will require that the maximum rod average burnup exceeds the current regulatory limit of 62 GWd/MTU, and it could peak at approximately 75 GWd/MTU, posing potential reactor safety and performance concerns. One such concern is that fuel fragmentation, relocation, and dispersal (FFRD) could occur during a severe loss-of coolant accident (LOCA) in which a fuel rod balloons and bursts, and pulverized fuel fragments are dispersed throughout the reactor’s primary coolant system. Previous analyses have identified which reactor operating conditions leave the core more susceptible to FFRD and have shown that FFRD susceptibility is strongly linked to fuel rod burnup and linear heat rate (LHR) history. The work described in this report uses an optimization strategy known as parallel simulated annealing (PSA) and a coarse mesh Purdue Advanced Reactor Core Simulator (PARCS) reactor physics model to develop two core fuel loading patterns, each with a different optimization objective. One core optimization maximized the core’s cycle length while still respecting regulatory limits on the radial peaking factor and soluble boron concentration with a peak rod average burnup of 75 GWd/MTU. The second optimization was aimed at minimizing FFRD susceptibility while still targeting a 24-month cycle length and respecting regulatory limits. PARCS model predictions were verified using the high-fidelity Virtual Environment for Reactor Applications (VERA). The two core designs were compared to highlight core design strategies to minimize FFRD susceptibility and to maximize economic viability.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
IEA PVPS Task 13 Techno-Economic Study of Bifacial Photovoltaic Systems on Single Axis Trackers
The International Energy Agency PVPS Task 13 has assembled an international team of photovoltaic (PV) researchers from government labs, academia, and industry to study the specific application of bifacial PV modules deployed on tracking systems. This configuration is of particular interest as it has been identified as the PV system design with the lowest Levelized Cost of Electricity (LCOE) for over 90% of the world [1]. As such, much research, development, and commercial activity are focused on further optimizing this system design for different regions and markets, including field deployment and advanced modeling activities. Despite these efforts, many challenges remain to overcome with this system design. This conference paper will report on several areas the team is working on as part of this project. The first part of this study focuses on extensive interviews with PV tracker companies (we have identified 35) and customers worldwide to identify emerging technology trends, design diversity, market environments, and the reliability and performance of these systems. We will provide a market summary of technologies such as advanced tracking algorithms, methods for dealing with topography within the PV plant, different system configurations and layouts, backside irradiance optimization from albedo enhancement, and ground sculpting. We will also review dual-use applications of tracked bifacial systems, such as Agrivoltaics and Building-Integrated PV. These interviews are underway now, and we will be able to report our initial findings at the conference. The second part of the study focuses on summarizing performance monitoring and evaluation methods, with particular attention to capacity and acceptance testing for such systems. The third part of the study reviews performance modeling and yield assessment methods for these tracked bifacial PV systems. The final part of the study covers reliability and operations, and maintenance data from these systems.
albedo↗
Reference Command Optimization for the Transition Flight Mode of a Lift plus Cruise Vehicle
Advanced air mobility mainly utilizes vehicles that are capable of vertical takeoff and landing (VTOL) for the simplicity of operation and large-scale deployment. However, VTOL vehicles need specialized trajectory and command design for the transition phase, where the vehicles transition between rotor-borne flight and wing-borne flight. Since VTOL vehicles are commonly designed as over-actuated systems for redundancy, one challenge that arises is actuator ambiguity, where it is unclear how to uniquely command actuators for the VTOL vehicle to track a given trajectory. We propose a method to design optimal reference commands for the transition mode. By formulating an 𝑙 1 -norm cost function on the rotor thrusts of the vehicle, we can achieve economical operation of the rotors such that they only operate when necessary and efficiently utilize the aerodynamics to save energy from reduced rotor actuation. We validate our approach in simulations and show its benefit compared to the commonly used differential flatness-based method.
John L Bullock↗
Advanced Integrated Power and Attitude Control System (IPACS) study
Integrated Power and Attitude Control System (IPACS) studies performed over a decade ago established the feasibility of simultaneously satisfying the demands of energy storage and attitude control through the use of rotating flywheels. It was demonstrated that, for a wide spectrum of applications, such a system possessed many advantages over contemporary energy storage and attitude control approaches. More recent technology advances in composite material rotors, magnetic suspension systems, and power control electronics have triggered new optimism regarding the applicability and merits of this concept. This study is undertaken to define an advanced IPACS and to evaluate its merits for a space station application. System and component designs are developed to establish the performance of this concept and system trade studies conducted to examine the viability of this approach relative to conventional candidate systems. It is clearly demonstrated that an advanced IPACS concept is not only feasible, but also offers substantial savings in mass and life-cycle cost for the space station mission.
Oglevie, R. E.↗
Fast, Safe, Propellant-Efficient Spacecraft Motion Planning Under Clohessy-Wiltshire-Hill Dynamics
This paper presents a sampling-based motion planning algorithm for real-time and propellant-optimized autonomous spacecraft trajectory generation in near-circular orbits. Specifically, this paper leverages recent algorithmic advances in the field of robot motion planning to the problem of impulsively actuated, propellant- optimized rendezvous and proximity operations under the Clohessy-Wiltshire-Hill dynamics model. The approach calls upon a modified version of the FMT* algorithm to grow a set of feasible trajectories over a deterministic, low-dispersion set of sample points covering the free state space. To enforce safety, the tree is only grown over the subset of actively safe samples, from which there exists a feasible one-burn collision-avoidance maneuver that can safely circularize the spacecraft orbit along its coasting arc under a given set of potential thruster failures. Key features of the proposed algorithm include 1) theoretical guarantees in terms of trajectory safety and performance, 2) amenability to real-time implementation, and 3) generality, in the sense that a large class of constraints can be handled directly. As a result, the proposed algorithm offers the potential for widespread application, ranging from on-orbit satellite servicing to orbital debris removal and autonomous inspection missions.
spacecraft relative motio↗
Photovoltaic Analysis and Response Support (PARS) Platform for Solar Situational Awareness and Resiliency Services
The project's primary objective is to develop a digital-twin based Photovoltaic (PV) Analysis and Response Support (PARS) platform, which aims to provide real-time situational awareness and optimal response plans. This platform is designed to enhance the performance of hybrid PV systems, making them competitive with or even superior to conventional generation resources. The PARS platform enabled the project team to develop and evaluate an extensive suite of grid support functionalities for the hybrid PV systems to enhance grid performance, across key areas including visibility, dispatchability, security, resilience, and reliability. Given the global push toward achieving 100% clean energy by 2035, there is a significant increase in the integration of inverter-based resources (IBRs) throughout the energy grid. Effectively managing the inherent variability and uncertainty associated with IBRs is crucial for ensuring cost-effectiveness, reliability, and security in both the main grid and islanded microgrids. Constrained to a limited array of IEEE test systems or standard feeder models, traditional IBR modeling struggles to assimilate new field data, accurately reflect system dynamics, and adapt to the evolving energy landscape. In our project, we embraced a Digital Twin (DT) strategy for crafting the PARS platform. A digital twin acts as a precise virtual counterpart of a physical system, built on historical data and continuously honed with real-time insights. This enables the high-fidelity DT to accurately mirror current system operations and forecast future scenarios. Consequently, the PARS platform becomes an ideal environment for testing and refining monitoring, control, power, and energy management algorithms designed to boost hybrid PV system performance. The defining feature of the PARS platform, distinguishing it from other advanced simulation tools, is its exceptional adaptability. This is achieved by employing actual network topologies and utilizing real-time field data for fine-tuning and calibration, ensuring a close emulation of real-world conditions. The project deliverables include: 1) High-fidelity IBR models and tools for real-time parameterization, utilizing real-time field measurements to refine IBR models for enhanced accuracy and performance; 2) Grid-forming and Grid-following capabilities to deliver resilience services, including blackstart, voltage and frequency support, cold-load pick-up, power reserves, and three-phase load balancing across grid-connected and microgrid settings; 3) Machine learning-based forecasting tools and methods for generating synthetic data and topologies, creating diverse and realistic simulation environments for evaluating varied operational scenarios; 4) Advanced microgrid power and energy management algorithms for optimizing the integration and operation of PV, storage, and demand response resources within both feeder and community scales. The power grid data sets are provided by four utility companies in North Carolina and the New York Power Administration. Acting as industry advisors, our industry partners communicated stakeholder needs and regulatory standards to the research teams, aiding technology transfer by incorporating the developed methodologies into their daily operations. This collaboration ensures that the PARS platform, functioning as a power system digital twin, enhances our understanding of IBR dynamic behaviors and enables the development and evaluation of IBR control functions that match or exceed the capabilities of conventional synchronous generators.
14 SOLAR ENERGY↗
Impacts and emerging research opportunities in Vehicle-Grid Integration for transportation: A review
This review provides a comprehensive examination of Vehicle-Grid Integration (VGI) technologies and their impacts on transportation systems, with a particular emphasis on the transportation-energy nexus. It systematically explores how VGI affects key transportation applications such as charging infrastructure planning, electric vehicle (EV) routing, smart charging coordination, shared mobility, and dynamic pricing. By synthesizing recent literature from both transportation and energy systems perspectives, this study highlights how advanced methodologies, such as reinforcement learning, game theory, and optimization techniques, are used to model the complex interactions between EVs, mobility patterns, and distributed energy systems. Furthermore, the review also identifies critical challenges, including behavioral factors, data limitations, and system scalability. Drawing on these insights, the paper outlines emerging research opportunities to support the design of integrated, resilient, and user-centric VGI solutions that advance sustainable mobility and energy system efficiency.
Charging coordination↗
Control co-design of commercial building chiller plant using Bayesian optimization
Not Available
Bhattacharya, Arnab↗
Accelerating Climate Resilient Plant Breeding by Applying Next-Generation Artificial Intelligence
Breeding crops for high yield and superior adaptability to new and variable climates is imperative to ensure continued food security, biomass production, and ecosystem services. Advances in genomics and phenomics are delivering insights into the complex biological mechanisms that underlie plant functions in response to environmental perturbations. However, linking genotype to phenotype remains a huge challenge and is hampering the optimal application of high-throughput genomics and phenomics to advanced breeding. Critical to success is the need to assimilate large amounts of data into biologically meaningful interpretations. Here, we present the current state of genomics and field phenomics, explore emerging approaches and challenges for multiomics big data integration by means of next-generation (Next-Gen) artificial intelligence (AI), and propose a workable path to improvement.
59 BASIC BIOLOGICAL SCIENCES↗