Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “market 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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment in the Area of Aluminum Alloys for AM Powder Production (Final Report)

The overall Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment (“X-P4AM”) project objective is to drastically reduce the time-to-market barriers for new additive alloys of interest in automotive and aerospace applications, through computational alloy design with rapid screening and down- selection via synthesis of candidate alloys with rapid solidification. The project will also refine the technology in high pressure gas atomization to improve the production of commercial quantities of selected powders with high powder yields and enhanced powder quality. A new aluminum (Al) alloy based on an Al-Ce-X composition, enhanced powder production, and optimized AM build parameterization provided a critical step in widespread adoption of AM technology for automotive applications, in this case. The individual background and capabilities of the Party are ideally suited to the successful execution of this work. The included work enhanced the Contractors’ AM capabilities, a core competency of the Contractors, and developed a close working relationship with the Participant in the area of aluminum powder alloys and their end use.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Evaluating advanced nuclear fission technologies for future decarbonized power grids

Advanced nuclear fission, which encompasses various innovative nuclear reactor designs, could contribute to the decarbonization of the United States electricity sector. However, little is known about how cost-competitive these reactors would be compared to other technologies, or about which aspects of their designs offer the most value to a decarbonized power grid. We employ an electricity system optimization model and a case study of a decarbonized U.S. Eastern Interconnection circa 2050 to generate initial indicators of future economic value for advanced reactors and the sensitivity of future value to various design parameters, the availability of competing technologies, and the underlying policy environment. These results can inform long-term cost targets and guide near-term innovation priorities, investments, and reactor design decisions. We find that advanced reactors should cost $\$5.7$–$\$7.3$/W to gain an initial market share (assuming 30 year asset life and 3.5 %–6.5 % real weighted average cost of capital), while those that include thermal storage in their designs can cost up to $\$6.0$/W–$\$7.7$/W (not including cost of storage). Since the marginal value of advanced fission reactors declines as market penetration increases, break-even costs fall ~32 % at 100 GW of cumulative capacity and ~51 % at 300 GW. Additionally, policies that provide investment tax credits for nuclear energy create the most favorable environment for advanced nuclear fission. In conclusion, these findings can inform near-term resource allocation decisions by stakeholders, innovators and investors working in the energy technology sector.

Capacity expansion↗
DOE OSTI2020

Catalytic Bio-crude Production in a Novel, Short-Contact Time Reactor

RTI has developed a catalytic fast pyrolysis (CFP) process to produce biomass-based hydrocarbon replacement fuels. From a technology perspective, this advanced biofuels process produces liquid transportation fuels that can leverage capital expenditures in the existing petroleum distribution infrastructure. From a business perspective, this technology does not face potential market limitations caused by oxygenate blend limitations for light duty vehicle applications. A promising catalyst has been developed with excellent potential for deoxygenation to produce a hydrocarbon-rich biocrude that is more suitable for upgrading with traditional hydroprocessing technology. The role of the catalyst is to control the chemistry during biomass pyrolysis to produce a biocrude in a single step that has lower oxygen content and is more thermally stable than conventional biomass fast pyrolysis oil. Catalyst properties are optimized to minimize gas and coke production and improve catalytic deoxygenation and biocrude yields. Results from this project have demonstrated that biocrudes from catalytic fast pyrolysis contain <20 wt% oxygen, with the organic fraction as low as 12% oxygen. These oxygen numbers are > 50% lower compared to traditional fast pyrolysis oils. The biocrude produced from our CFP process can be upgraded to gasoline range hydrocarbons. A very conservative approach for upgrading included a preliminary stabilization step followed by a hydroprocessing step. The oxygen content in the upgraded product was decreased by 97% (to less than 3wt %) from the oxygen content of the biocrude sample. Additionally, the acid content was reduced by 99% from the acid content of the biocrude sample. In an optimized integrated process, the CFP step and the hydroprocessing (upgrading) step need to be carefully balanced to maximize the input biomass energy that is recovered in the finished biofuels. Hydrogen utilization and carbon recovery during both catalytic biomass pyrolysis and biocrude upgrading need to be optimized to maximize energy recovery in the finished biofuel. A nominal 1 ton per day (TPD) catalytic biomass pyrolysis system was designed based on the laboratory experimental data. The system was designed to achieve the short residence times (0.5–2 sec) and high heat transfer rates required for maximum liquid biocrude yields while optimizing process integration to maintain catalyst activity by continuous regeneration. The catalytic biomass pyrolysis reactor is a continuously circulating single-loop transport reactor design that is flexible enough to allow sensitivity studies around temperature, residence time, biomass feed rate, and catalyst-to-biomass ratio (i.e., catalyst circulation rate) for process optimization. For a nominal 100 lb/hr feed rate of dry biomass, the products include ~25 lb/hr char and coke, ~20 lb/hr permanent gases, and ~55 lb/hr condensable vapors. Pyrolysis temperatures are 350–600°C, and the system is operated close to ambient pressure. Production of the catalyst developed within the project was scaled up to provide enough material (200kg) for bench-scale testing. The 1TPD bench-scale unit was fabricated, installed and commissioned with this project. Biocrude samples from wood were produced in this unit with the CFP catalyst with material balance > 90%. The intermediate biocrude yields and chemical composition compare well with previous laboratory results and a hydroprocessing strategy for upgrading the resulting biocrude was developed. The experimental results obtained within this project were used to develop a process model for a 2000 TPD commercial facility. Detailed flow sheets were developed for all major unit operations in the process and provided a basis for an economic analysis to develop capital and operating costs. Estimates of the biofuel production costs were used to develop internal rates of return for the yields and compositions measured for the current state of technology at the end of this project and for the yields anticipated for an optimized (nth plant) scenario as additional process improvements are made.

09 BIOMASS FUELS↗
DOE OSTI2024

Nuclear Thermal Energy Storage Configurations for Industrial Combined Heat and Power Supply: Conceptual Study and Engineering Designs

The industries examined in this report primarily rely on moderate-temperature heat provided by gas- or coal-fired boilers and combined heat and power (CHP) plants, delivered through standard process steam systems. High-temperature energy demands are often industry-specific and typically exceed the capabilities of high-temperature gas-cooled reactors (HTGRs). While it is technically feasible to replace process steam from fossil-based heat sources with nuclear energy, certain industries, such as methanol production and pulp and paper, face technoeconomic challenges in integrating nuclear energy without major changes or a technological shift. This is mainly due to the limited external energy demand remaining after the use of internal byproducts, waste heat recovery, and simple efficiency improvements. Achieving full decarbonization of these processes with nuclear energy would require significant technological advancements, involving experimental technology and substantial investments, making widespread adoption in existing industrial plants unlikely in the near term. This study reviews TES options in the context of enabling a flexible CHP supply while maintaining a steady nuclear heat input. Heat storage systems that interface between the reactor primary fluid and the CHP system offer superior performance and flexibility. Specifically, steam extraction downstream of the reheater with a two-tank molten-salt TES appears as the best solution regarding thermodynamic system benefits and system drawbacks. Using selected system configurations, a conceptual design of an industrial energy park was developed for industries with varying energy demands, such as steel production plants utilizing electric arc furnaces (EAFs) and chemical plants, as well as for those with constant energy demands, like petroleum refineries. This design highlights the capabilities of TES and explores its potential business cases. The study also conceptually develops the potential for integrating additional energy sources with nuclear systems through the implementation of TES. The potential of the HTGR-TES-CHP system was also evaluated considering key uncertainties such as industrial demand profiles, external grid access availability, and eligible tax credit levels, using the Holistic Energy Resource Optimization Network. Sensitivity of net present value to these uncertainties was analyzed to determine the optimal number of nuclear reactors (and CHP systems) and the suitable TES capacity. The results were interpreted from a decision-maker’s perspective, focusing on three key areas: deployment strategy (oversized units vs. undersized units with TES support), industrial process characteristics (thermal-intensive single profiles vs. electricity-intensive combined profiles), and operational goals (maximizing profits vs. minimizing natural gas (NG) consumption or external grid dependence). The optimization results indicate that the HTGR-TES-CHP system significantly reduces reliance on NG boilers for individual industrial processes by 9-60% (in NG capacity factor), with an average reduction of 38%, compared to standalone NG boiler operation case (Business As Usual [BAU]). For combined industrial processes, the reduction ranges from 37-77%, with an average of 60%. Additionally, the system greatly reduces dependence on external grids. In meeting industrial electrical demands, a 33-100% self-sufficient internal electricity supply is achieved for single industrial process, with an average of 74%, compared to the BAU scenario, where 100% of electricity is imported. For combined processes, 35-100% of internal electricity demands are met by the reactor, with an average of 73%. At last, the relative NG price levels at which the proposed HTGR-TES-CHP system can cost-effectively enter the market currently dominated by existing NG boilers were estimated. For a moderate HTGR CAPEX level ($\$$2500/kWth, $\$$6329/kWe), the analysis suggests that NG prices must be 2.5 to 7 times higher than HTGR variable operating and maintenance costs for single industrial process, and 5.5 to 9.5 times higher for a combined process scenario. Tax credit modeling shows that the Investment Tax Credit significantly reduces the price threshold needed to break even, making the system competitive with NG boilers in certain cases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Recipes for a Successful Exit for Clean- and Hard-tech Startups

This study demonstrates the combinations of multiple causal factors that formulate a startup’s strategy to successfully “exit”, namely “recipes for a successful exit,” in the clean- and hard-tech sector. We identify seven key causal factors (i.e., causal conditions) that impact startup success, including commercial readiness, investor interactions, favorable industry, non-financial support, straightforward development path, experienced team, and visibility to investors. We also investigate the combinations of selective causal conditions that can provide further synergetic impact. We conduct the fuzzy-set qualitative comparative analysis (fsQCA) on seven US clean and hard-tech startups that exited between 2005 and 2016. The successful companies all demonstrate distinctive characteristics based on three general categories (1) robust ecosystem; (2) heavy-lifting team; or (3) external opportunity. Across these three categories, commercial readiness and strong investor interactions are necessary conditions for all exit cases. But there are important differences that drive success in each category, such as the interaction with non-financial support (in the robust ecosystem case), experienced team (in the heavy-lifting team case), and favorable industry (in the external opportunity case). Furthermore, our findings are meant to support entrepreneurs in reaching an exit by optimizing the given internal and external circumstances, and policymakers to build a robust ecosystem that can increase the success rate of the clean- and hardtech development.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Double Deep Q-Networks for Optimizing Electricity Cost of a Water Heater

Electric water heaters represent 14% of the electricity consumption in the residential buildings and the cost associated with domestic water heating account for a good portion of the household expenses in the United States. In this context, intelligent control of water heaters gained a lot of research attention. In recent years, a significant number of intelligent water heater controllers, with various methods and intended uses, have been proposed. However, existing studies are mostly model-based approaches that require an accurate modelling of the water heater. Towards addressing this research gap, this paper presents a model-free reinforcement learning-based controller for a day-ahead price market. The controller aims to minimize the cost of domestic water heating while maintaining the user comfort. The results showed that the developed controller can help save energy cost while maintaining the temperatures within the desired comfort band.

Amasyali, Kadir↗
DOE OSTI2020

Opportunities for Clean Energy in Natural Gas Well Operations

The oil and gas industry is increasingly seeking operational improvements to reduce both costs and emissions while improving resilience against electric grid outages. This study describes techno-economic analysis of opportunities for distributed energy generation and storage technologies to support companies’ energy cost savings, clean energy, and energy resiliency goals. Specifically, the analysis evaluates solar photovoltaics (PV), distributed wind energy, and battery energy storage at hypothetical upstream well sites in the Marcellus Shale in Pennsylvania, both grid-connected and off-grid. Results indicate opportunity for solar PV to reduce operational costs. Additionally, these technologies reduce the site’s consumption of grid electricity and natural gas and thus can help reduce Scope 1 and 2 emissions associated with electricity and natural gas consumption. For each emissions reduction scenario, a cost of avoided emissions was calculated; these values can be compared to internal organizational value placed on emissions reductions, compared to other emissions reduction strategies such as energy efficiency, reducing flaring, and direct carbon capture and sequestration, and compared to existing (albeit limited) U.S. carbon markets such as California’s Low Carbon Fuel Standard. Results indicate that the associated costs of emissions reductions via distributed renewables are competitive with these options and markets. The study also explores the ability of these electric clean energy technologies to support site resiliency against utility outages.

42 ENGINEERING↗
DOE OSTI2020

Opportunities for Clean Energy in Natural Gas Well Operations

The oil and gas industry is increasingly seeking operational improvements to reduce both costs and emissions while improving resilience against electric grid outages. This study describes techno-economic analysis of opportunities for distributed energy generation and storage technologies to support companies' energy cost savings, clean energy, and energy resiliency goals. Specifically, the analysis evaluates solar photovoltaics (PV), distributed wind energy, and battery energy storage at hypothetical upstream well sites in the Marcellus Shale in Pennsylvania, both grid-connected and off-grid. Results indicate opportunity for solar PV to reduce operational costs. Additionally, these technologies reduce the site's consumption of grid electricity and natural gas and thus can help reduce Scope 1 and 2 emissions associated with electricity and natural gas consumption. For each emissions reduction scenario, a cost of avoided emissions was calculated; these values can be compared to internal organizational value placed on emissions reductions, compared to other emissions reduction strategies such as energy efficiency, reducing flaring, and direct carbon capture and sequestration, and compared to existing (albeit limited) U.S. carbon markets such as California's Low Carbon Fuel Standard. Results indicate that the associated costs of emissions reductions via distributed renewables are competitive with these options and markets. The study also explores the ability of these electric clean energy technologies to support site resiliency against utility outages.

42 ENGINEERING↗
DOE OSTI2024

A Highly Efficient and Affordable Hybrid System for Hydrogen and Electricity Production (Final Project)

The pursuit of clean, secure, and sustainable energy has sparked significant interest in fuel cells for power generation and electrolyzer cells for hydrogen production. Among all types of fuel and electrolyzer cells, solid oxide cells (SOCs) have emerged as promising candidates due to their high efficiency and versatility. However, conventional oxygen-ion conductive SOCs face several challenges related to their performance and durability associated with their high-temperature operation (≥ 800 ºC). This has led to a growing interest in intermediate-temperature (≤ 650 ºC) proton-conducting solid oxide cells (p-SOCs) as potential alternatives. In collaboration between Phillips 66 and Georgia Tech, this project aims to achieve a 1 kW p-SOCs system to demonstrate the commercial viability of efficient SOC systems. This report addresses four primary areas and key challenges we overcame: (1) development of efficient and durable proton-conducting electrolyte (e.g., BaHf 0.1 Ce 0.7 Yb 0.2 O 3-δ ) and electrode/catalyst materials, (2) large area cell fabrication (10 x 10 cm 2 ), (3) scalable stack design and building (250 W and 1 kW), and (4) demonstration of a 1 kW prototype system. Notably, significant challenges faced during the large area cell fabrication process were addressed by achieving cell flatness, improving fabrication yield, and ensuring electrode/electrolyte interfacial adhesion. Stack designs were also developed, focusing on reducing contact resistance and optimizing stack components (e.g., sealants). These efforts resulted in the achievement of high performance and durability with promising outputs of 250 W and 1 kW. Furthermore, the integration of these stacks into a fuel-powered system was explored, with refinements made to heat management, as well as to pressure and heating conditions. The results demonstrated the potential applicability of our p-SOC technology in commercial energy storage and power generation systems. Additionally, the report discusses techno-economic analysis and a market transformation plan, aiming to evaluate and advance the commercial feasibility of this technology.

25 ENERGY STORAGE↗
DOE OSTI2020

Learning to Solve Large-Scale Security-Constrained Unit Commitment Problems

Security-constrained unit commitment (SCUC) is a fundamental problem in power systems and electricity markets. In practical settings, SCUC is repeatedly solved via mixed-integer linear programming (MIP), sometimes multiple times per day, with only minor changes in input data. In this work, we propose a number of machine learning techniques to effectively extract information from previously solved instances in order to significantly improve the computational performance of MIP solvers when solving similar instances in the future. Based on statistical data, we predict redundant constraints in the formulation, good initial feasible solutions, and affine subspaces where the optimal solution is likely to lie, leading to a significant reduction in problem size. Computational results on a diverse set of realistic and large-scale instances show that using the proposed techniques, SCUC can be solved on average 4.3 times faster with optimality guarantees and 10.2 times faster without optimality guarantees, with no observed reduction in solution quality. Out-of-distribution experiments provide evidence that the method is somewhat robust against data-set shift. Summary of Contribution. The paper describes a novel computational method, based on a combination of mixed-integer linear programming (MILP) and machine learning (ML), to solve a challenging and fundamental optimization problem in the energy sector. The method advances the state-of-the-art, not only for this particular problem, but also, more generally, in solving discrete optimization problems via ML. We expect that the techniques presented can be readily used by practitioners in the energy sector and adapted, by researchers in other fields, to other challenging operations research problems that are solved routinely.

Machine Learning↗
DOE OSTI2023

Modeling and simulation to investigate the electrification potential of medium- and heavy-duty vehicle fleets

This project involves developing and integrating new modeling tools to simulate the dynamics of electric medium- and heavy-duty fleet vehicle adoption. A technical and economic modeling tool, combining a data-driven hardware cost model with a cost-optimal charging strategy microsimulation, enables tailored analysis of the costs and benefits of electrifying individual fleets. Next, a novel text synthesis process, applied to a curated corpus of literature, quantifies trade-offs between technical, economic, and other factors in the fleet vehicle procurement decision. The outcomes of these tasks combine with knowledge from recent literature on fleet decision processes to specify the vehicle procurement model used by fleets in an agent-based model of the medium- and heavy-duty electric vehicle market. This model embodies an especially disaggregated approach to adoption modeling, internalizing factors and dynamics that conventional adoption models externalize. In particular, explicitly modeling the formation and diffusion of opinions among agents enables experiments that conventional models cannot support. Demonstrations show, for example, that increasing the extent of interactions between populations with different proclivities to electric vehicles has an asymmetrical outcome. High-proclivity electric vehicle adoption is generally unaffected as interactions increase, but low-proclivity adoption is accelerated. By representing individual fleets' requirements and costs at a high level of detail, incorporating an adoption decision model informed by a wide body of empirical research, and broadening the array of variables and dynamics available for experimentation, this integrated model offers a new way to understand the urgent challenge of eliminating emissions from the most emissions-intensive transportation sectors.

Trinko, David A.↗
DOE OSTI2020

Re-Envisioning RCx: Achieving Max Potential HVAC Controls Retrofits through Modernized BAS Hardware and Software

Most existing buildings have sub-optimal heating, ventilation, and air conditioning (HVAC) controls, resulting in wasted energy and occupant discomfort. Retro-commissioning (RCx) addresses many of these issues, but it is a lengthy and highly customized process. Limited capabilities of existing building automation system hardware restricts the scope of most RCx projects. Incentive programs consider building automation system (BAS) hardware retrofits to be high-capital investments and do not allow them in typical RCx programs. This paper describes work that the authors are leading to facilitate technical and market innovation in the BAS industry to unlock large savings in existing commercial buildings through deep retrofits of BAS hardware and software. California and New York research projects are demonstrating BAS retrofits leveraging the American Society of Heating, Refrigeration, and Air Conditioning Engineers’ (ASHRAE) new Guideline 36 high performance sequences of operation to achieve greater than 20 percent whole building energy savings, while saving costs and reducing risk through streamlined processes and standardization across BAS manufacturer product lines and across implementation practices. This paper describes market barriers that impede achieving deep savings from BAS retrofits in custom incentive and traditional RCx programs and presents a new maximum potential BAS retrofit model that addresses these barriers. The new model leverages the authors’ efforts in market enablement through open standards, BAS industry partnerships, and tools for cost-effective scaling that includes tools for project screening, savings calculations, and measurement and verification (M&V). This approach is widely applicable and will be ready for at-scale implementation within two years.

Paliaga, Gwelen↗
DOE OSTI2021

Predicting Deformation of Parts from HP Printers due to Sintering with Modeling and Simulation (CRADA NFE-18-07363)

This work proposes to leverage Oak Ridge National Laboratory’s (ORNL) sintering simulation software developed at the Manufacturing Demonstration Facility to 1) investigate the deformation of sintered parts and 2) to develop fast surrogate-based optimization methods for HP Inc. This includes the development of ORNL’s software on HP systems, integration and testing with HP part geometries and material properties, the development of surrogate models based on the results of the simulation, and modifications to the software based on feedback from HP. The expected impacts of this work are a drastic reduction in print costs, an increase in printer throughput, and the identification of novel, possibly exotic materials for 3D printing. This work will also decrease the time to market for HP’s print technology by decreasing the amount of resources and type dedicated to physical testing.

42 ENGINEERING↗
DOE OSTI2023

Science-Based Acceleration of the Full Value Stream for Metal Additive Manufacturing: Expedited Powder Development and Additive Manufacturing Deployment in the Areas of Ni-Base Superalloy and Custom Alloy Powders for AM (Final Report)

The overall Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment (“X-P4AM”) project objective is to drastically reduce the time-to-market barriers for new additive alloys of interest in automotive and aerospace applications, through computational alloy design with rapid screening and down- selection via synthesis of candidate alloys with rapid solidification. The project will also refine the technology in high pressure gas atomization to improve the production of commercial quantities of selected powders with high powder yields and enhanced powder quality. Production of modified nickel-based superalloys and a Ni-containing alloy based on a high entropy composition, enhanced powder production methods, and optimized AM build parameterization provided critical steps in widespread adoption of AM technology for aerospace applications, in this case. The individual backgrounds and capabilities of the Parties are ideally suited to the successful execution of this work. The included work enhanced the Contractors’ AM capabilities, a core competency of the Contractors, and develop a close working relationship with the Participant in the area of nickel-based powder superalloys and custom alloys and their end use.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Science-Based Acceleration of the Full Value Stream for Metal Additive Manufacturing: Expedited Powder Development and Additive Manufacturing Deployment in the Areas of Ni-Base Superalloy and Custom Alloy Powders for AM

The overall Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment (“X-P4AM”) project objective is to drastically reduce the time-to-market barriers for new additive alloys of interest in automotive and aerospace applications, through computational alloy design with rapid screening and down- selection via synthesis of candidate alloys with rapid solidification. The project will also refine the technology in high pressure gas atomization to improve the production of commercial quantities of selected powders with high powder yields and enhanced powder quality. Production of modified nickel-based superalloys and a Ni-containing alloy based on a high entropy composition, enhanced powder production methods, and optimized AM build parameterization provided critical steps in widespread adoption of AM technology for aerospace applications, in this case. The individual backgrounds and capabilities of the Parties are ideally suited to the successful execution of this work. The included work enhanced the Contractors’ AM capabilities, a core competency of the Contractors, and develop a close working relationship with the Participant in the areas of nickel-based powder superalloys and custom alloys and their end use.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Science-Based Acceleration of the Full Value Stream for Metal Additive Manufacturing: Expedited Powder Development and Additive Manufacturing Deployment in the Areas of Ni-Base Superalloy and Custom Alloy Powders for AM

The overall Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment (“X-P4AM”) project objective is to drastically reduce the time-to-market barriers for new additive alloys of interest in automotive and aerospace applications, through computational alloy design with rapid screening and down- selection via synthesis of candidate alloys with rapid solidification. The project will also refine the technology in high pressure gas atomization to improve the production of commercial quantities of selected powders with high powder yields and enhanced powder quality. Production of modified nickel-based superalloys and a Ni-containing alloy based on a high entropy composition, enhanced powder production methods, and optimized AM build parameterization provided critical steps in widespread adoption of AM technology for aerospace applications, in this case. The individual backgrounds and capabilities of the Parties are ideally suited to the successful execution of this work. The included work enhanced the Contractors’ AM capabilities, a core competency of the Contractors, and develop a close working relationship with the Participant in the areas of nickel-based powder superalloys and custom alloys and their end use.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Regularized Variance-Reduced Modified Extragradient Method for Stochastic Hierarchical Games

We consider an N -player hierarchical game in which the i th player’s objective comprises of an expectation-valued term, parametrized by rival decisions, and a hierarchical term. Such a framework allows for capturing a broad range of stochastic hierarchical optimization problems, Stackelberg equilibrium problems, and leader-follower games. We develop an iteratively regularized and smoothed variance-reduced modified extragradient framework for iteratively approaching hierarchical equilibria in a stochastic setting. We equip our analysis with rate statements, complexity guarantees, and almost-sure convergence results. We then extend these statements to settings where the lower-level problem is solved inexactly and provide the corresponding rate and complexity statements. Our model framework encompasses many game theoretic equilibrium problems studied in the context of power markets. We present a realistic application to the study of virtual power plants, emphasizing the role of hierarchical decision making and regularization. Preliminary numerics suggest that empirical behavior compares well with theoretical guarantees.

Tikhonov regularization↗
DOE OSTI2026

Effectively Considering the Distribution System in Integrated Resource Plans

While electricity planning practices vary by state and utility based on utility type and market structure, integrated resource planning (IRP) remains a prominent vehicle — even in states with centrally-organized wholesale electricity markets. IRP focuses on meeting forecasted long-term electricity needs. Typically, utilities have not considered impacts of design and operation of the low-voltage distribution network in IRP. With advanced capabilities of grid-edge technologies to generate and store electricity and provide load flexibility, and large utility investments in distribution systems, it's increasingly important to consider at least some distribution planning elements in IRP. This report considers the value proposition for doing so, such as reducing utility costs through resource co-optimization and strategic siting of grid-edge resources, and idenfities the most important touchpoints between planning for bulk power and distribution systems and provide a range of tactics for integrating these two processes.

Relf, Grace [Lawrence Berkeley National Laboratory↗