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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

US EPA Superfund Remediation Program Update: Revisions to Risk and Dose Assessment Models - 20368

The U.S. Environmental Protection Agency (EPA) Superfund remedial program is finishing up a significant number of revisions to its guidance for the risk assessment process at radioactively contaminated Superfund sites. The six Preliminary Remediation Goal (PRG) and Dose Compliance Concentration (DCC) internet-based calculators for radiation risk and dose assessment at Superfund sites are being reformatted to match the chemical calculators and improve the user experience, revised to add a new peak risk and dose output option, and to add some adjustment options for external exposure. A new Radon Vapor Intrusion Screening Level (RVISL) calculator is expected to be finished in 2020, will be similar to the Vapor Intrusion Screening Level (VISL) for chemical calculator that was finished in 2018. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Data for An End-to-End Pipeline for Succinic Acid Production at an Industrially Relevant Scale Using Issatchenkia orientalis

Microbial production of succinic acid (SA) at an industrially relevant scale has been hindered by high downstream processing costs arising from neutral pH fermentation for over three decades. Here, we metabolically engineer the acid-tolerant yeast Issatchenkia orientalis for SA production, attaining the highest titers in sugar-based media at low pH (pH 3) in fed-batch fermentations, i.e. 109.5 g/L in minimal medium and 104.6 g/L in sugarcane juice medium. We further perform batch fermentation using sugarcane juice medium in a pilot-scale fermenter (300×) and achieve 63.1 g/L of SA, which can be directly crystallized with a yield of 64.0%. Finally, we simulate an end-to-end low-pH SA production pipeline, and techno-economic analysis and life cycle assessment indicate our process is financially viable and can reduce greenhouse gas emissions by 34–90% relative to fossil-based production processes. We expect I. orientalis can serve as a general industrial platform for production of organic acids.

Metabolomics↗
DOE OSTI2020

Recovery of High Purity Rare Earth Elements (REE) from Coal Ash via a Novel Electrowinning Process (Final Report)

The goal of this project was to produce a high purity, separated (>90%) rare earth oxide (REO) product from coal-based sources. This product was achieved using the following three steps: 1. Battelle’s ADP: The ADP process involves pretreatment of ash (milling and caustic leaching), leaching of pretreated ash with nitric acid, roasting of loaded acid solution containing REE, and water leaching of residual from roasting step, resulting in a REE pregnant solution. 2. Solvent Extraction (SX) Upgrading: The SX involves the extraction of REE from a pregnant REE solution using an organic extractant (note after extraction, the aqueous phase was a residual solution and the organic phase contained REE), and stripping of REE from the organic phase product obtained from the extraction using an acid solution (the stripped solution was the final purified product containing REE, organic traces, and traces of other metals for further separation in the electrowinning process). 3. Rare Earth Salts’ (RES) Electrochemical Separation and Purification Process: The staged electrochemical process was separated REO products from the mixed REE solution. Testing by RES was also included in the investigation of options to minimize the solvent extraction steps. This report covers laboratory testing, production of a high purity coal-based REO, process design of the overall REE recovery and purification process, technoeconomic assessment (TEA), and a commercialization plan discussing the overall REE recovery and purification process.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Development of a Technical, Economic, and Risk Assessment Tool for the Evaluation of Work Reduction Opportunities

Efficient and cost-effective operation of a nuclear power plant (NPP) is essential to ensuring long-term economical and safe operation. Multiple cost saving opportunities exist, referred to here as work reduction opportunities (WRO). These WROs reduce plant operating costs by employing various cost-effective strategies (e.g., implementation of modern technologies). Identifying and objectively screening WROs is an essential task to help reduce overall costs. However, there is no comprehensive framework for assessing WROs in the nuclear industry and evaluating their impact on plant operations. This report presents a novel framework for systematically evaluating WROs from a technical, economic, and risk perspective. As NPPs continue to add new technology and implement modernization strategies into their current processes, potential WROs are commonly identified. Although most WROs have the potential to reduce costs, not all opportunities will result in significant cost savings due to unforeseen risks, large implementation costs, or benefits that fall short of expectations. Examples of this can be the result of a technology that is not fully developed, uncertainty in the amount of cost reduction, or difficulties introducing a new process into an organization. These uncertainties can manifest several ways and can result in a WRO with limited cost savings or even a loss of investment. The framework developed emphasizes the importance of effectively screening the WROs from a holistic perspective to objectively identify inefficiencies and ensure a positive impact to the organization. This report presents the Technical, Economic, and Risk Assessment (TERA) as a key methodology for the screening and evaluation of potential WROs. The TERA framework begins with a screening phase where the process is examined through a hybrid combination of Lean Six Sigma and Integrated Operations for Nuclear (ION) guiding principles. This framework examines the current processes using the Lean Six Sigma SIPOC (Suppliers, Inputs, Process, Outputs, Consumers) methodology but retains the ION key elements of People, Technology, Process, and Governance as important factors to the nuclear decision-making process. By combining the principles of Lean Six Sigma and ION, the developed screening process is specific to the nuclear industry in that it systematically evaluates WROs in order to implement new technology that is comprehensively evaluated. The TERA begins by mapping current processes as they relate to WROs and examining the inefficiencies. Furthermore, the created process map can be used to identify and evaluate potential solutions. Using key performance indicators (KPIs), the TERA evaluates each area—technology, economics, and risk—for uncertainties and to perform cost-benefit analysis. The results of the TERA are important KPIs that allow for an evaluation of different processes and technology implementations. This assessment enables decision-makers to compare various WROs based on metrics and then make informed decisions for which opportunity to implement first. This research includes not only the creation of the TERA framework, but also the evaluation of its performance. A case study for screening potential WROs at Southern Nuclear Company is presented that utilizes the TERA methodology. Through the use of TERA, various WROs were screened, and the solutions evaluated for cost-benefit expectations. The report concludes by summarizing the overall effort and implications for utility modernization. The performance of the screening and TERA are discussed as well as the impact on the nuclear industry. The TERA process enables utilities to evaluate and inform investment decisions for WROs and mitigate any potential risks. Through this research, we provide utilities with a valuable framework to optimize operations, reduce costs, and drive continuous process improvement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Feasibility of using nuclear microreactor process heat for bioconversion and agricultural processes

Introduction There is a global goal to reduce greenhouse gas emissions by 43% by 2023. Nuclear microreactors, a subset of small modular reactors, offer a potential solution due to their compact size, transportability, and carbon-neutral power generation capabilities. Methods This study explores the feasibility of using heat from nuclear microreactors for bioconversion and agricultural processes, including transforming biomass into energy carriers and products such as syngas, bio-oil, and pasteurized milk. Operating requirements for gasification, pyrolysis, hydrothermal carbonization, hydrothermal liquefaction, hydrothermal gasification, ethanol production, anaerobic digestion, and pasteurization were obtained through a literature review. A Brayton cycle model based on the eVinci TM microreactor was developed to assess the feasibility of powering these processes using nuclear microreactor heat. Results and Discussion Exergetic efficiency values for high-temperature processes ranged from 72% to 100%, whereas lower-temperature processes ranged from 2% to 53%. These efficiencies depend on the available source temperature for each microreactor design. There were trade-offs between producing net power and using process heat, particularly for high-temperature processes. Three heat exchanger locations were considered: before the turbine (600 ℃ ), between the turbine and regenerator (370 ℃ ), and after the regenerator (192 ℃ ). High-temperature processes like gasification require temperatures too high for feasibility. Middle temperature processes are better suited to a heat exchanger between the turbine and regenerator, while also operable before the turbine. Lower-temperature processes like pasteurization and anaerobic digestion can use waste heat after the regenerator and do not impact power production. These findings are valuable for optimizing nuclear microreactor heat use and aligning with global climate initiatives.

09 BIOMASS FUELS↗
DOE OSTI2020

Risk Informed, Performance-Based, Technology-Inclusive Regulatory Infrastructure: Technology-Inclusive Determination of Mechanistic Source Terms for Offsite Dose-Related Assessments for Advanced Nuclear Reactor Facilities

This report summarizes a risk informed, performance-based and technology-inclusive approach to determine source terms for dose related assessments at advanced nuclear facilities. This approach uses a graded process which allows both the non-mechanistic source terms calculation methods, which adopt conservative approaches and assumptions based on known physical and chemical principles, and more importantly the mechanistic source term calculation methods, which consider design-specific scenarios and use best estimate models with uncertainty quantification for a range of licensing basis events (LBEs), to be used for the design and licensing of advanced nuclear technologies. The source terms developed with this graded approach, and radionuclide inventories elsewhere in the facility that are determined during source term analysis, can be used to address licensing issues to support the application processes of 10 CFR Part 50 for a construction permit and operating license or 10 CFR Part 52 for a Combined Operating License (COL), Standard Design Certification, Early Site Permit, Standard Design Approval or Manufacturing License. They can also be used for other purposes including equipment environmental qualification, control room habitability analyses, and assessments of severe accident risks in environmental impact statements. There are many advanced reactor concepts being developed including high temperature gas-cooled reactor (HGTR), sodium-cooled fast reactor (SFR), lead-cooled fast reactor (LFR), molten salt reactor (MSR), micro-reactor, etc. The graded approach presented in this report for source terms determination is, to the extent possible, generic to any of these reactor designs and to future reactor designs. This report provides information on the review of the regulatory foundation for use of conservative bounding source terms as well as event-specific mechanistic source terms for advanced nuclear reactor designs.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Grain size estimation in fluvial gravel bars using uncrewed aerial vehicles: A comparison between methods based on imagery and topography

Abstract Grain size assessments are necessary for understanding the various geomorphological, hydrological and ecological processes that occur within rivers. Recent research has shown that the application of Structure‐from‐Motion (SfM) photogrammetry to imagery from uncrewed aerial vehicles (UAVs) shows promise for rapidly characterising grain sizes along rivers in comparison to traditional field‐based methods. Here, we evaluated the applicability of different methods for estimating grain sizes in gravel bars along a study reach in the Olentangy River in Columbus, Ohio. We collected imagery of these gravel bars with a UAV and processed those images with SfM photogrammetry software to produce three‐dimensional point clouds and orthomosaics. Our evaluation compared statistical models calibrated on topographic roughness, which was computed from the point clouds, and to those based on image texture, which was computed from the orthomosaics. Our results showed that statistical models calibrated on image texture were more accurate than those based on topographic roughness. This might be because of site‐specific patterns of grain size, shape and imbrication. Such patterns would have complicated the detection of topographic signatures associated with individual grains. Our work illustrates that UAV‐SfM approaches show potential to be used as an accessible method for characterising surface grain sizes along rivers at higher spatial and temporal resolutions than those provided by traditional methods.

Wong, Tyler↗
DOE OSTI2025

Microstructural Assessment of Molybdenum Disulfide Coatings Using Nanoindentation Hardness

MoS 2 coatings are used extensively in aerospace and defense applications due to their ultralow friction and high wear resistance. Burnished and resin-bonded MoS 2 coatings are commonly used in these applications due to simplicity in deposition and history of use, despite issues with consistency in coating properties and performance. Physical vapor deposition (PVD) of MoS 2 thin films has emerged as a process alternative in the past 50 years, promising far greater control over film structure and composition but at a greater cost. Despite PVD’s benefits, hesitance to adoption persists in high-consequence applications, not only due to increased costs but variability in resulting coating properties. These variations in properties and subsequent performance are in part due to the complexity of the PVD process and the sensitive interplay between coating process-structure-property relationships. This work aims to demystify the remaining uncertainties of the process-structure-property relationships in PVD MoS 2 . The microstructure and mechanical and tribological properties of 61 different PVD pure MoS 2 coatings are examined herein. Emphasis has been placed on developing performance-based (i.e., hardness, modulus) metrics that can assess microstructural changes (density, orientation, and crystallinity) and be utilized to accelerate process development and coating optimization. Relationships established within suggest that nanoindentation hardness can be used to infer coating performance (i.e., wear rate) and properties (i.e., density, crystalline texture, and stoichiometry). Furthermore, this work demonstrates that PVD MoS 2 coatings close to the theoretical density of MoS 2 consistently have the best tribological performance and can be reliably identified by their hardness.

MoS2↗
DOE OSTI2021

A Hybrid Energy System Workflow for Energy Portfolio Optimization

This manuscript develops a workflow, driven by data analytics algorithms, to support the optimization of the economic performance of an Integrated Energy System. The goal is to determine the optimum mix of capacities from a set of different energy producers (e.g., nuclear, gas, wind and solar). A stochastic-based optimizer is employed, based on Gaussian Process Modeling, which requires numerous samples for its training. Each sample represents a time series describing the demand, load, or other operational and economic profiles for various types of energy producers. These samples are synthetically generated using a reduced order modeling algorithm that reads a limited set of historical data, such as demand and load data from past years. Numerous data analysis methods are employed to construct the reduced order models, including, for example, the Auto Regressive Moving Average, Fourier series decomposition, and the peak detection algorithm. All these algorithms are designed to detrend the data and extract features that can be employed to generate synthetic time histories that preserve the statistical properties of the original limited historical data. The optimization cost function is based on an economic model that assesses the effective cost of energy based on two figures of merit: the specific cash flow stream for each energy producer and the total Net Present Value. An initial guess for the optimal capacities is obtained using the screening curve method. The results of the Gaussian Process model-based optimization are assessed using an exhaustive Monte Carlo search, with the results indicating reasonable optimization results. The workflow has been implemented inside the Idaho National Laboratory’s Risk Analysis and Virtual Environment (RAVEN) framework. The main contribution of this study addresses several challenges in the current optimization methods of the energy portfolios in IES: First, the feasibility of generating the synthetic time series of the periodic peak data; Second, the computational burden of the conventional stochastic optimization of the energy portfolio, associated with the need for repeated executions of system models; Third, the inadequacies of previous studies in terms of the comparisons of the impact of the economic parameters. The proposed workflow can provide a scientifically defendable strategy to support decision-making in the electricity market and to help energy distributors develop a better understanding of the performance of integrated energy systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Chemical-Free Lithium Separation from High-Salinity Brines Using Model-Informed and Machine Learning-Optimized Multi-Column Zwitterionic Chromatography

Direct Lithium Extraction (DLE) technologies often struggle to produce high-purity lithium salts from high-salinity brines, as current approaches require chemical-based elution, regeneration, and precipitation steps, resulting in significant environmental footprints. A novel salt fractionation approach using carboxybetaine resin, known as zwitterionic chromatography (ZIC), has demonstrated that lithium ions can be separated from divalent cations under high-salinity conditions using only water as eluent, with no regeneration required. To enable continuous and scalable deployment of this approach, we developed a chemical-free Multi-column Zwitterionic Chromatography (MZC) process and its theoretical and process models. To predict and optimize this nontraditional separation system, we introduced a novel anti-Langmuir isotherm, and the isotherm parameters were estimated through a machine learning-driven optimization based on artificial neural network ensembles with numerical feasibility assessment. Using machine learning-driven optimization, the MZC process achieved 98.0% lithium recovery, 99.5 % Li/(Li + Mg + Ca) purity, a 31.3% productivity increase, and a 33% reduction in water use compared to batch operation. The proposed MZC process enables lithium separation at $0.6-1.2 kg-1 Li, with costs dominated by resin manufacturing, while offering lower separation costs and carbon footprint compared with conventional carbonation. Overall, these findings position the MZC process as an effective polishing step within scalable and sustainable lithium production pipelines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Host Onboarding Tool (HObT) v1.0.0

The Host OnBoarding Tool (Hobt) is a publicly accessible, web-based software designed to organize and share information about microbial hosts under development at the Agile BioFoundry (ABF). It streamlines the assessment, tracking, and sharing of information related to microbial host development and provides a centralized platform where users can rapidly evaluate hosts' readiness for various bio processes. HObT leverages the Tier System, a standardized host development framework that organizes and assesses microbial hosts based on their readiness for biomanufacturing. Each tier outlines key targets—including genetic tools, growth conditions, omics data, and predictive models—needed to transform new or emerging microbes into established production platforms. By applying clear criteria for advancement, the Tier System helps users quickly evaluate each organism's current development status, identify gaps in available knowledge or tools, and prioritize future strain improvement efforts. Through its user-friendly interface, HObT encourages contributions of new data and insights from researchers, fostering collaboration and accelerating host development. By providing structured guidance for microbial strain advancement, HObT and the Tier System support more systematic, rapid, and cost-effective development of non-traditional microbial hosts, ultimately enhancing the efficiency and impact of biomanufacturing research and applications.

Plahar, Hector [Lawrence Berkeley National Laborat↗
DOE OSTI2020

On the Formalization of Development and Assessment Process for Digital Twins in the Nearly Autonomous Management and Control System

In recent years, the autonomous control system has been encouraged in advanced reactors for restoring economic viability, simplifying the operation and maintenance, and enabling remote-site power generations [1]. Since the reactor is expected to be operated for a long period of time with a limited number of individuals onsite, it is recommended that the autonomous control system should have access to very realistic models of the state of processes in the whole lifecycle, together with these process behaviors in interaction with their environment in the real world. As a result, digital twin (DT) technology is suggested in autonomous control systems. DT is defined as a digital representation of a physical object or system, which contains a record for the histories of loads, operation and maintenance status, predictions for the near-term transient of important state variables, and decision-making process [2]. Since machine learning (ML) can recognize patterns within a complex system in real-time applications, it has been used to build DTs in the autonomous control systems for advanced reactors. Meanwhile, due to the rareness of operation data in accident scenarios, the development and assessment of DTs is expected to be mainly driven by simulations. Although the capability and feasibility of ML-based DTs are recognized in improving the safety and efficiency of reactor control, a major concern from the regulatory commission and the nuclear industry is whether the information from a DT is developed and assessed in accordance with expectation and requirements by the target decision. Such concerns not only affect the acceptance criteria for DTs, but also values that can be extracted from DTs and autonomous control system during operations. Inspired by the success of formal methods in improving the reliability and robustness of computer programming and software development, it is suggested that the development and assessment process (DAP) for both separate DTs and integral control system should be formalized in a transparent, consistent, and improvable manner. In this study, a digital-twin development and assessment process (DT-DAP) is proposed by adapting the evaluation model development and assessment process (EMDAP) [3] to requirements by the autonomous control system, ML algorithms, and DT technology. To demonstrate the framework, a baseline nearly autonomous management and control (NAMAC) system with ML-based DTs for diagnosis and prognosis is developed and assessed based on the framework. It is found that with selected testing methods and techniques, the DT-DAP can help identify errors in DTs and NAMAC which would otherwise be left unverified. Meanwhile, it is found that the DT-DAP can improve the DTs and NAMAC by continuously learning and iterating through different elements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Cost of Using Laser Powder Bed Fusion to Fabricate a Molten Salt-to-Supercritial Carbon Dioxide Heat Exchanger for Concentrating Solar Power

Advances in manufacturing technologies and materials are crucial to the commercial deployment of energy technologies. We present the case of concentrating solar power (CSP) with molten salt (MS) thermal storage, where low-cost, high-efficiency heat exchangers (HXs) are needed to achieve cost competitiveness. Here, the materials required to tolerate the extreme operating conditions in CSP systems make it difficult or infeasible to produce them using conventional manufacturing processes. Although it is technically possible to produce HXs with adequate performance using additive manufacturing, specifically laser powder bed fusion (LPBF), here we assess whether doing so is cost-effective. We describe a process-based cost model (PBCM) to estimate the cost of fabricating a MS-to-supercritical carbon dioxide HX using LPBF. The PBCM is designed to identify modifications to designs, process choices, and manufacturing innovations that have the greatest effect on manufacturing cost. Our PBCM identified HX design and LPBF process modifications that reduced projected HX cost from $\$750$ per kilo-Watt thermal (kW-th) ($\$8$ /cm 3 ) to $\$350$ /kW-th ($\$6/$ cm 3 ) using currently available LPBF technology, and down to $\$220$ /kW-th ($\$4$ /cm 3 ) with improvements in LPBF technology that are likely to be achieved in the near term. The PBCM also informed a redesign of the HX design that reduced projected costs to $\$140$ –160/kW-th ($\$3$ /cm 3 ).

36 MATERIALS SCIENCE↗
DOE OSTI2020

Analysis of a Fluidized-Bed Particle/Supercritical-CO2 Heat Exchanger in a Concentrating Solar Power System

Concentrating solar power (CSP) development has focused on increasing the energy conversion efficiency and lowering the capital cost. To improve performance, CSP research is moving to high-temperature and high-efficiency designs. One technology approach is to use inexpensive, high-temperature heat transfer fluids and storage, integrated with a high-efficiency power cycle such as the supercritical carbon dioxide (sCO 2 ) Brayton power cycle. The sCO 2 Brayton power cycle has strong potential to achieve performance targets of 50% thermal-to-electric efficiency and dry cooling at an ambient temperature of up to 40 °C and to reduce the cost of power generation. Solid particles have been proposed as a possible high-temperature heat transfer or storage medium that is inexpensive and stable at high temperatures above 1000 °C. The particle/sCO 2 heat exchanger (HX) provides a connection between the particles and sCO 2 fluid in emerging sCO 2 power cycles. This article presents heat transfer modeling to analyze the particle/sCO 2 HX design and assess design tradeoffs including the HX cost. The heat transfer process was modeled based on a particle/sCO 2 counterflow configuration, and empirical heat transfer correlations for the fluidized bed and sCO 2 were used to calculate heat transfer area and estimate the HX cost. A computational fluid dynamics simulation was applied to characterize particle distribution and fluidization. This article shows a path to achieve the cost and performance objectives for a particle/sCO 2 HX design by using fluidized-bed technology.

14 SOLAR ENERGY↗
DOE OSTI2020

Rapid Response Data Science for COVID-19

This report describes the results of a seven day effort to assist subject matter experts address a problem related to COVID-19. In the course of this effort, we analyzed the 29K documents provided as part of the White House's call to action. This involved applying a variety of natural language processing techniques and compression-based analytics in combination with visualization techniques and assessment with subject matter experts to pursue answers to a specific question. In this paper, we will describe the algorithms, the software, the study performed, and availability of the software developed during the effort.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Cyber-Resilient Design Methodology for Microgrids

Recent advancement in tools has helped with microgrid design, development, planning and operation. Microgrids offer a unique application based on users with different requirements for tools. The process of designing, constructing, commissioning, and assessing a microgrid is not always straightforward due to these distinct requirements. Additionally, metrics are needed for performance evaluation. This panel will offer an overview and description of tools that helps with microgrid design, construction, planning, operation, cyber security, and metrics-driven performance assessment driven by multiple diverse applications and use cases.

CCE↗
DOE OSTI2024

Performance assessment of near-fault buildings subjected to physics-based simulated earthquake ground motions with fling step

The effects of the co-seismic static offset (known as fling step) and associated velocity pulses on civil structures have been difficult to study because the static offset is typically removed during the processing of earthquake ground motion records. Simulated ground motions contain fling features and require no processing; therefore, they create new opportunities for representing fling features in seismic hazard analysis and assessing their influence on the seismic demands on near-fault structures. We use physics-based fault rupture simulations to study the characteristics of ground motions with fling step and the sensitivity of the near-fault structural demands to strong fling features. We uncover that simulated ground motions with a large fling step tend to have higher spectral intensity than those without a fling step at the same rupture distance, especially at periods longer than 2 s. As a result, the structural demands on flexible buildings tend to be the most sensitive to the fling features. Statistical analysis suggests that the ground motion spectral shape (represented by spectral accelerations at multiple periods) is—in most cases—a sufficient predictor of the structural demands on near-fault low-rise and mid-rise buildings at locations that are susceptible to strong fling effects. Finally, ground motion record selection experiments reveal that representing the spectral shape features at periods that are most relevant to a given structure may be an effective strategy to reduce the bias in the estimated demands on near-fault long-period structures when the available database of records is considered deficient in fling features.

Fling step↗
DOE OSTI2020

Process Heating Assessments Using DOE’s Manufacturing Energy Assessment Software for Utility Reduction (MEASUR) Tool Suite

Process heating is the most energy-intensive manufacturing process for most sectors of industry. To quantify energy savings from various energy conservation measures, the Department of Energy (DOE) sponsored the development of the Process Heating Assessment and Survey Tool (PHAST) and similar tools for other industrial systems in the early 2000s. It has been used extensively in the Save Energy Now Program’s Energy Savings Assessments and the Better Plants Program’s In-Plant Trainings. Since the initial development of the legacy tools, both computer operating systems and software development have evolved significantly. Thus, DOE has invested in the modernization of PHAST and other legacy software tools to create the Manufacturing Energy Assessment Software for Utility Reduction (MEASUR) tool suite. MEASUR offers a collection of software tools that can aid manufacturing facilities in improving the efficiency of energy systems and equipment (specifically pumps, fans, steam, and process heating) and in conducting “Energy Treasure Hunts”. Eventually, the tool will also add compressed air and process cooling systems. The Process Heating Assessment (PHA) module of MEASUR is an upgrade of the PHAST tool. PHA provides the means to model fuel-fired, steam-based, and electric process heating systems, covering process heating for most industrial plants in manufacturing sector. It also includes several key upgrades, including the ability to consider multi-component charge loads and account for several different areas of energy losses. The new tool includes a comprehensive flue gas calculator to quantify available heat and heat loss for various gaseous, liquid, and solid fuels and new heat loss calculators. It generates a report and a dynamic Sankey diagram to show the energy consumption in various areas of energy use. MEASUR has significantly improved the user experience by adopting a modern software design. This paper details the structure and workflow of PHA and presents a real-world case study to demonstrate energy savings quantification and MEASUR’s outstanding reporting capabilities.

Nimbalkar, Sachin U.↗