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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

What Rocks and What's Not So Hot: U.S. Industry Perception of Geothermal Tax Credits

Nationwide, four U.S. federal tax credits promote the adoption of geothermal heat pumps (GHPs) and geothermal power plants and were recently updated with enactment of the Inflation Reduction Act (IRA).1 However, uptake of these geothermal tax credits has lagged behind other eligible technologies.2 With the support of the U.S. Department of Energy (DOE)'s Geother- mal Technologies Office, researchers at the National Renewable Energy Laboratory (NREL) engaged with the geothermal industry to determine: 1) how the industry will use the tax credits, 2) remaining challenges to utilizing tax credits, and 3) suggestions on solutions that could help accelerate tax credit uptake. Insights were obtained through two industry question- naires (59 responses)3 and 21 interviews with representatives from geothermal industry groups, project developers, com- ponent manufacturers, and financiers, as shown in Figures 1 and 2. This article synthesizes the industry's perception of these tax credits, i.e., Section 25D (residential GHP), Section 48 (commer- cial GHP), Section 48E (investment tax credit [ITC] for electricity), and Section 45Y (production tax credit [PTC] for electricity).

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Optimizing Energy Use in Pulp & Paper with DOE’s Energy Intensive Industries Resources

The U.S. pulp and paper industry is the third-largest energy consumer in manufacturing, accounting for roughly 10% of sector energy use. Improving energy efficiency reduces operating costs and strengthens competitiveness. To support this effort, the U.S. Department of Energy (DOE), through Oak Ridge National Laboratory (ORNL), launched the Energy Intensive Industries (EII) Initiative. A two-year pilot across 45 industrial sites identified more than 4 trillion Btu/year in potential energy savings. This presentation outlines plans for a follow-up technical assistance program tailored to pulp and paper mills. Available resources include a cost-savings scoping tool, implementation planning guidance, and technical support for applying advanced methods such as Pinch Analysis for integrated process-utilities optimization. The session introduces key Pinch Analysis principles and highlights case studies demonstrating measurable improvements. ORNL also seeks industry feedback on barriers to efficiency improvements, including technology gaps and resource needs. DOE’s broader objective is to accelerate productivity and economic competitiveness across U.S. energy-intensive industries.

Kamath, Dipti [ORNL] (ORCID:0000000278739994)↗
DOE OSTI2024

The role of AI in detecting and mitigating human errors in safety-critical industries: A review

For safety-critical industries, human error (HE) presents continual risks to system productivity, reliability and safety. Artificial intelligence (AI) and machine learning (ML) methods have emerged as promising approaches to understand, categorize and mitigate the risk of HE in safety-critical industries. Furthermore, this review offers an examination of the current landscape regarding the utilization of AI/ML with regards to HE in safety-critical industries, categorizing literature into descriptive modeling, predictive modeling, prescriptive modeling, and generative modeling techniques. Additionally, the review aims to provide insights regarding themes in literature, challenges, and future research directions. Findings of the review suggest that AI/ML methods can prove useful in addressing the HE problem across safety-critical industries.

42 ENGINEERING↗
DOE OSTI2025

Automated Fire Detection for Industrial Settings with Pretrained Convolutional Networks

Early fire detection in industrial environments is critical to preventing equipment damage, personal injury, and operational disruptions. Traditional smoke detectors, while effective, often experience delays due to the time required for smoke to reach sensors, allowing fires to spread. Manual fire watch operations and human surveillance of camera feeds are resource-intensive and prone to human error. To address these challenges, this paper explores the application of convolutional neural networks for automated fire detection, specifically in industrial settings. By leveraging 11 different pre-trained machine vision models from TensorFlow and enhancing them with transfer learning on a custom-built industrial fire dataset, we optimized fire detection performance. Here, we analyzed each machine vision model architecture in terms of its depth, width, and input image resolution, considering both resource requirements and detection accuracy. We further explored the option of combining multiple models into an ensemble classifier to evaluate whether the performance improvements could justify the much greater computational complexity and other practical impacts. A cost-benefit analysis is presented to evaluate the trade-offs between performance and computational expense. Our findings identify that EfficientNetV2L, specifically tailored for industrial applications, provides the optimal balance between costs involved in training and using the model versus the overall fire detection performance. Additionally, we present a qualitative analysis of model performance using the technique of gradient-based class activation mapping to provide explainability by visualizing model decisions.

artificial intelligence↗
DOE OSTI2022

Dynamic optimization with flexible heat integration of a solar parabolic trough collector plant with thermal energy storage used for industrial process heat

There is an increasing need to reduce fossil fuel consumption used for industrial process heat to slow the effects of climate change. Using solar thermal heat is a viable way to replace fossil fuel use, but solar industrial process heat plants have limited implementation due to large upfront costs and inefficiencies from the inherent variability from solar energy. Having more flexible and optimized control over these plants can enable them to be more efficient. Here in this work, a solar industrial process heat plant with thermal energy storage that can flexibly collect and deliver heat to two industrial processes (flexible heat integration) is dynamically modeled with control setpoints found by a dynamic optimization method. The optimized case can increase the solar efficiency of the plant by 7.5% on average relative to a base case. The results show that it is best to collect heat at lower temperatures for all but ideal solar conditions, only medium to high quality heat should be stored in large quantities, and exchanging heat with a lower temperature heat sink is generally more efficient. The optimized case is able to reduce the levelized cost of heat of the plant to $31.83/MWh th compared to a base case value of $34.10/MWh th . The optimized case can reduce emissions by 22.2% compared to a plant which uses only natural gas. This work shows that dynamic optimization with flexible heat integration can be a cost-effective way to increase efficiency so that more of these types of plants can be implemented.

14 SOLAR ENERGY↗
DOE OSTI2022

The pursuit of net-positive sustainability for industrial decarbonization with hybrid energy systems

We report signatories of the Paris Agreement are set to miss their climate targets. The net-zero pledges announced to date across many countries and private industries are insufficient to achieve carbon neutrality, which requires implementation of far-reaching and significantly scaled-up climate-positive actions. All technology options that pertain to deep decarbonization and carbon removal must be part of the mitigation portfolio. Transformative action plans must be established in which every individual/organization around the globe is an actor of changes in relation to net-zero goals. Such plans must involve governmental policy support but also encourage voluntary efforts to boost innovations, investments, initiatives, and behavioral changes. Recognition of these efforts is made quantifiable with the concepts of carbon handprint and net positivity. This paper presents a carbon handprint perspective on characterizing the environmental benefits of hybrid energy systems (HESs)—a widely applicable solution to cleaner production leveraging the capabilities of a portfolio of low-carbon energy sources—that provide heat and electricity to industrial processes. First, the carbon handprint and net positivity concepts and their calculation approach are introduced. The state of the art of HES-enabled industrial cogeneration is then surveyed, and the greenhouse gas emission intensities of different energy sources that power HESs are compared. Next, drawing on a case study about a US chemical facility's voluntary initiative to explore replacing its fossil fuel–based cogeneration infrastructure with a clean energy–generated HES, several technically viable scenarios are evaluated—especially those with small modular nuclear reactors—to illustrate how the positive-thinking handprint approach helps encourage and inform the search for widespread influence pathways in pursuit of net-positive sustainability. Finally, current knowledge gaps in the case study are identified, and opportunities to scale up the proposed handprint-based analysis are outlined with consideration of an expanded role of HESs in fulfilling climate objectives.It is envisioned that like-minded decision makers in the industry sector and beyond will adopt this perspective and act synergistically to enhance their environmental stewardship through voluntary actions and make greater contributions to the planet's climate future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Techno-economic design of a linear Fresnel reflector for industrial process heat

A techno-economic model of a Concentrating Solar Thermal (CST) system using a Linear Fresnel Reflector (LFR) has been developed. LFRs can deliver process heat suitable for a range of industries, including food and beverage production. This model uses an adaptive algorithm to calculate the optimal secondary reflector shape given the geometry and optical properties of the rest of the system. A ray-tracing program is used to calculate optical efficiency over a wide range of longitudinal and transversal incidence angles and subsequently evaluate the annual efficiency at a given geographical location. A specific LFR design developed by Hyperlight Energy was modelled, and this industrial partner provided a detailed cost breakdown which was used as the basis of an economic model. Combining the technical and economic data facilitates the calculation of the Levelized Cost of Heat (LCOH). The influence of a number of parameters on the annual efficiency and LCOH is explored; notable parameters include the absorber height, the number, width, and spacing of the primary mirrors, the aim point, and the secondary reflector shape and width. By identifying an optimal combination of these parameters, we reduce the LCOH of the industry partner’s system design by 9.2%, from 14.4 $\$/MWh_{th}$ to 13.0 $\$/MWh_{th}$. In comparison, the LCOH of a natural gas boiler delivering the same annual quantity of heat is 29 $\$/MWh_{th}$, which indicates that LFRs can be a competitive heat source for industrial processes.

14 SOLAR ENERGY↗
DOE OSTI2022

UF Industrial Assessment Center - Budget Periods 2017-2021. Final Report

This report summarizes the work performed at the University of Florida’s Industrial Assessment Center (UF-IAC) during the five budget periods (BPs) in the years 2017 through 2021 under DOE Award No. DE-EE0007707. The objective of the work is to perform industrial assessments to small- and medium-sized manufacturing facilities in the State of Florida and to train students in industrial energy management and in performing industrial assessments. Specific details about the activities of the UF-IAC (referred to as the Center) during that time can be found in the 20 quarterly reports that were submitted throughout the duration of the contract. The project start and end dates are September 1, 2016 and August 31, 2021, respectively. The project was granted a six-month no-cost extension till February 28, 2022, to accommodate unexpected delays due to the COVID-19 pandemic. This project was performed by the University of Florida (PI: Dr. SA Sherif). The scope of work includes six milestone whose description and outcomes are listed in the Statement of Project Objectives (SOPO).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Renewable Thermal Energy Systems: Characterization of the Most Important Thermal Energy Applications in Buildings and Industry (Report 1)

This report is the first in a three-report series that evaluates the provision of renewable heat for industry and buildings via current and prospective renewable thermal energy system (RTES) technologies. The RTES project has undertaken initial research focused on technologies that could be suited for industrial process heat applications at different temperature levels, and, where possible, gathered performance and cost data for these technologies. This project does not directly evaluate RTES for distributed residential or commercial applications, nor does it yet include documented cases or modeling of RTES using geothermal, biomass, waste heat, renewable fuels like renewable natural gas, or hydrogen production. The three technical reports are summarized as follows: Renewable Thermal Energy Systems: Characterization of the Most Important Thermal Energy Applications in Buildings and Industry (Report 1), this report: summary of thermal demands of U.S. industry and buildings, and relevant hybrid RTES configurations; Renewable Thermal Energy Systems: Systemic Challenges and Transformational Policies (Report 2): discussion of socio-technical characteristics of RTES, innovation challenges, and supporting policies. Available at: https://www.nrel.gov/docs/fy23osti/83020.pdf; Renewable Thermal Energy Systems: Modeling Developments and Future Directions (Report 3): Energy yield and performance modeling of RTES, techno-economic analysis via case studies, and proposed development of a user decision support tool. Available at: https://www.nrel.gov/docs/fy23osti/83021.pdf.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

A Comparative Study of Machine Learning Algorithms for Industry-Specific Freight Generation Model

According to Bureau of Transportation Statistics, the U.S. transportation system handled 14,329 million ton-miles of freight per day in 2020. Understanding the generation of these freight shipments is crucial for transportation researchers, planners, and policymakers to design and plan for a more efficient and connected freight transportation system. Traditionally, the freight generation modeling has been based on Ordinary Least Square (OLS) regression, although more advanced Machine Learning (ML) algorithms have been evaluated and proven to have excellent performance in various transportation applications in recent years. Furthermore, one modeling approach applied for one industry might not always be applicable for another as their freight generation logics can be quite different. The objective of this study is to apply and evaluate alternative ML algorithms in the estimation of freight generation for each of 45 industry types. Seven alternative ML algorithms, along with the base OLS regression, were evaluated and compared. In addition, the study considered different combinations of variables in both the original and logarithmic form as well as hyperparameters of those ML algorithms in the model selection for each industry type. The results showed statistically significant improvements in the root mean square error reduction by the alternative ML algorithms over the OLS for over 80% of cases. The study suggests utilizing the alternative ML algorithms can reduce the root mean square error by about 30%, depending on industry types.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Assessment of Survey Results from Advanced Reactor Industry Domain Experts on Nonlinear Soil-Structure Interaction Analysis Software Verification and Validation

The seismic load case has a significant impact on the design and cost of nuclear power plants. Given the need to substantially reduce cost, advanced reactor designers are looking to leverage numerical tools that enable seismic analysis of an integrated vessel/support/structure/soil system. Modern nonlinear analysis tools provide a solution, capturing dynamic coupling between components (including soil-structure interaction (SSI)) concurrent with nonlinear behavior in one or more parts of the system. Although these methods have a rich history of technical development and implementation, software quality assurance (SQA) following nuclear industry standards remains a significant burden for those wishing to adopt such methods for advanced reactor design and licensing. To reduce the SQA burden, this project will develop the guidance for SQA verification and validation (V&V) of coupled nonlinear SSI analysis tools, to include a test matrix of software features and test problems to support commercial grade dedication (CGD). The guidance is intended to be technology-neutral: supporting designers of all advanced reactors. To maximize the value of the project to reactor designers, the project team performed focused surveys of and interviews with advanced reactor designers. Additionally, the project surveyed members of the broader industry involved in reactor design and licensing. The aggregated industry feedback consists of written survey responses, live polling responses, focused interviews, and informal feedback provided after outreach presentations, collectively referred to as “survey results”. Herein, the survey results are reported, reviewed, and assessed to inform follow-on project activities. The survey results confirmed the familiarity of the industry with the coupled nonlinear SSI analysis. They also affirm the project need based upon the expressed intent to (1) incorporate nonlinear features and (2) pursue the coupled nonlinear SSI analysis to reduce seismic demands and construction costs. All reactor designers indicated their intent to incorporate two or more nonlinear features, and all reactor designer respondents opined that the coupled nonlinear SSI analysis would allow for the optimization of the reactor design and construction. However, the programmatic challenges, whether real or perceived, present a significant barrier to reactor designers. The barrier most commonly identified by the reactor designer population was regulatory risk, with 70% citing this as a reason not to pursue the approach. The perceived regulatory risk identified by the reactor designers underscores the importance of regulator engagement and dialogue in this project. Additionally, half of the reactor designers identified cost and lack of guidance as a deterrent. The survey results also provide insights to tailor specific aspects of the guidance document and test matrix. The project plans to prepare both a formal referenceable guidance document and a collaborative, web-based test matrix and problem set. The project will focus on more complete test problem definitions for the prioritized nonlinear features over shallower problem descriptions for a larger set of features. The nonlinearities prioritized as high based upon survey feedback include fluid-structure interaction and seismic isolation and energy dissipation devices. The nonlinearities prioritized as intermediate include nonlinear geomaterials, nonlinear concrete, nonlinear steel, and interface/contact nonlinearity. Deep embedment and the associated nonlinear phenomena are assigned the lowest priority based upon survey feedback.

42 ENGINEERING↗
DOE OSTI2021

Opportunities for Solar Industrial Process Heat in the United States

This presentation summarizes the first national analysis of opportunities for solar technologies to provide industrial process heat (IPH) in the United States. The industrial sector is a major end-user of energy and IPH constitutes a majority of industrial fuel energy. New disaggregations of IPH demands are made at the temporal, geographic, and operational levels. Solar heat generation by seven solar thermal technologies and PV-connected electrotechnologies are modeled using county solar resources and land availability and matched to relevant IPH demands. Parabolic trough collectors (PTC), when combined with thermal energy storage (TES), not only have the largest opportunity in terms of distribution over geography and time, but also in terms of applicable IPH demands. PTC with TES represents the displacement of nearly 2,500 trillion Btus of combustion fuels, which corresponds to 137 million metric tons of CO2, or about 15% of all industrial combustion CO2 emissions. TES, along with site-level analysis, are identified as areas of further analysis.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2020

The Intern Professional Development Center: A Model for Improving Student Engagement Within Industry - 20006

Many innovations and technical improvements have been made over the last half-century regarding our understanding of nuclear materials, with some of the brightest minds in the world collectively working towards a cleaner, brighter, healthier future. However, there is a demographical oddity with the enormous technical workforce that helped shape this new world: they are aging, collectively. Known as the 'silver tsunami,' mass retirements are in the near future for many technical industries, something that the industrial community is not entirely prepared to accommodate. There is an urgent need for a tech-savvy generation to replace the baby boomers, and there must be an uninterrupted hand-off from one generation to the next of institutional knowledge and best practices. Further, it is not enough to simply replace every retiring engineer with a younger one in a 'cold hand-off' - this information transfer takes time. Many educational communities, such as those in the Tri-Cities, Washington, are rising to the challenge, with STEM-focused programs, introducing students to technical concepts and potential career opportunities at an early age. However, while individually, academic institutions search for internships and industry has open positions for interested students, no single clearinghouse exists in the Mid-Columbia region to match talent with opportunities, regardless of the sending or receiving organizations. To fill this void, AYB Drafting (AYB) has established a career development and personal growth center, the Intern Professional Development Center (IPDC). The IPDC, located in Richland, Washington, addresses the problem of what has been referred to as the 'Graying of America,' as it bridges the gap between education and career for the up and coming workforce, creating valuable efficiencies for the young workforce and the industry alike. The operating principles and details of the initial IPDC launch are discussed in the following text, as well as the apparent success and overwhelming positive feedback received in just the first year of operation. (authors)

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2026

Industry Growth Forum: Innovation and Investment

The Industry Growth Forum (IGF) is the premier convening for energy innovation entrepreneurs, investors, and industry leaders. Hosted by NLR, the nation's leading energy systems integration laboratory, the IGF leverages decades of technical expertise and industry partnerships to bring together promising startups and forward-thinking investors. Gain meaningful visibility and recognition of your organization as a sponsor at the 2026 Industry Growth Forum.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Key Strategies in Industry for Circular Economy: Analysis of Remanufacturing and Beneficial Reuse

Manufacturing, in the effort to be more sustainable, is increasingly focusing on energy efficiency and waste reduction. DOE's Better Buildings Better Plants Program has established Waste Reduction Network that works with 32 industrial partners to achieve higher material efficiency and reduce waste. United States generates 7.6 Billion Tons of industrial solid waste as estimated by EPA. In a linear economy as the economy grows, so does the waste – increasing strain on resources and the environment. The Circular Economy (CE) model keeps the available resources in circulation for longer period of time easing the burden on the environment.Remanufacturing and (Beneficial) reuse are widely accepted channels in 9R methodology and established pillars of CE. This chapter reviews the two key strategies and their adoption in different industrial sectors. It reviews the key barriers faced by manufacturers in implementing these methodologies and discusses the possible solutions to those barriers. The chapter also reviews impact of these CE strategies on sustainability, material efficiency and the economic and social benefits. Finally, this chapter presents two case studies from DOE's Better Plants partners – one on remanufacturing of components in heavy vehicles industry and one on beneficial reuse of spent foundry sand, a non-hazardous solid waste, and discusses the project impacts.

Chaudhari, Subodh↗
DOE OSTI2022

Strengthening Mechanisms and Deformation Behavior of Industrially-Cast and Lab-Cast Dual-Phase High Entropy Alloy

An iron-rich high entropy alloy Al 0.65 CoCrFe 2 Ni comprising of both FCC and BCC phases was designed and fabricated using induction melting at a large industrial scale and suction casting at a small lab scale. Spinodally decomposed interdendritic regions were uniformly distributed in the industrially melted alloy, and a finer dendritic structure with smaller sized spinodal structures was observed in the alloy suction cast at lab scale. The suction cast alloy fabricated at the lab scale exhibited significantly higher compressive yield strength compared to the industrially cast alloy. The relative strengthening contributions in the alloys due to solid solution, grain boundary, dislocation interactions and interphase boundary were analyzed. Dislocation hardening was the major contributor responsible for the higher strength of the SC alloy. The deformation behavior in the alloys was examined with the help of orientation image mapping. Finally, intense slip band formation at large strains in the industrially melted alloy indicates that cold working can be an effective technique to enhance the strength of the dual-phase high entropy alloy processed at a large scale.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Electrodeposited nickel coatings for exceptional corrosion mitigation in industrial grade molten chloride salts for concentrating solar power

Molten chloride salt eutectics are attractive candidates for use as thermal energy storage media and heat transfer fluids in generation-three concentrating solar thermal power (Gen3 CSP) plants. However, corrosion of alloys in molten chloride salts, especially at high temperatures, is an extremely challenging problem that studies focus on lower temperatures, shorter durations, or analytical grade, and high-purity, salts. To date, there has been no study on corrosion or corrosion mitigation in an industrial-grade salt at a high temperature such as 750 °C. To alleviate this knowledge gap, the study presents new multiscale fractal-textured Ni coatings on various alloy surfaces for effective corrosion mitigation at 750 °C in molten chloride salts. Using the electrodeposition method, durable double-layer textured coatings were formed on stainless steel alloys (SS316, SS310, and SS347) and In800H. The corrosion performance of the coatings is investigated in both analytical-grade purity and, for the first time, practically relevant industrial-grade chloride salts. Ni-coated ferrous alloys showed an exceptionally reduced corrosion rate in the range of 350–480 μm/y in analytical-grade salts, and between 450 and 490 μm/y in purified industrial-grade salts at 750 °C. Ni coatings on ferrous alloys reduced corrosion rates by as much as 70% compared to uncoated surfaces and were comparable to the expensive Ha230 alloy with a high Ni content. As a result, by the use of innovative fractal corrosion mitigation coatings, for the first time, low-cost structural alloys are rendered viable for use with industrial-grade chloride salts, which is profoundly beneficial in practical systems.

14 SOLAR ENERGY↗
DOE OSTI2021

Microbial drivers of methane emissions from unrestored industrial salt ponds

Wetlands are important carbon (C) sinks, yet many have been destroyed and converted to other uses over the past few centuries, including industrial salt making. A renewed focus on wetland ecosystem services (e.g., flood control, and habitat) has resulted in numerous restoration efforts whose effect on microbial communities is largely unexplored. We investigated the impact of restoration on microbial community composition, metabolic functional potential, and methane flux by analyzing sediment cores from two unrestored former industrial salt ponds, a restored former industrial salt pond, and a reference wetland. We observed elevated methane emissions from unrestored salt ponds compared to the restored and reference wetlands, which was positively correlated with salinity and sulfate across all samples. 16S rRNA gene amplicon and shotgun metagenomic data revealed that the restored salt pond harbored communities more phylogenetically and functionally similar to the reference wetland than to unrestored ponds. Archaeal methanogenesis genes were positively correlated with methane flux, as were genes encoding enzymes for bacterial methylphosphonate degradation, suggesting methane is generated both from bacterial methylphosphonate degradation and archaeal methanogenesis in these sites. These observations demonstrate that restoration effectively converted industrial salt pond microbial communities back to compositions more similar to reference wetlands and lowered salinities, sulfate concentrations, and methane emissions.

59 BASIC BIOLOGICAL SCIENCES↗