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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Radiometric Testing of Germicidal UV Products, Round 2: Upper-Room Luminaires (CALiPER Report)

This report analyzes the independently tested performance of eight germicidal ultraviolet (GUV) upper-room luminaires marketed for use in occupied spaces and purchased between March and June 2023. This type of product is mounted to upper walls or ceilings to treat air in the portion of the room above occupants; this allows for safe use of the room when the device is operating, but requires sufficient air mixing between upper and lower portions of the room. Three of the luminaires used UV-emitting LEDs, and the remaining five luminaires used low-pressure mercury (LPM) lamps. Product testing covered radiometric and electrical performance for each luminaire. Initial performance was measured for all eight products, and four were additionally measured after 100 h and 500 h of operation. Measured performance data allowed for comparison against manufacturer or vendor claims if the tested products included such claims. Some products had no performance data available for a given quantity (e.g., UV-C output power), and only four of the eight luminaires had radiant intensity distribution data files in a standard format (e.g., IES LM-63) available for download from product websites. The lack of publicly available performance data makes it difficult for potential buyers and specifiers to identify suitable products and design GUV systems for their specific applications. When products had performance claims, they were sometimes contradictory (e.g., unexplained differences between multiple power values) or ambiguous (e.g., measurement units conflict with quantity, unclear whether luminaire power or lamp power, unclear whether UV output power or UV-C output power). Three of the eight tested luminaires had claimed output power (i.e., radiant flux) values that exceeded measured values by more than an order of magnitude. There was substantial variation in UV-C radiant efficiency, with a measured range of 0.3–1.9% for LED and 0.4–2.1% for LPM, as shown in Figure 1. For example, the LPM luminaire with 0.4% radiant efficiency would need 5 times the amount of electrical energy used by the LPM luminaire with 2.1% radiant efficiency to produce the same amount of UV-C output power. LPM luminaires that had parabolic reflectors aligned with inclined louvers exhibited substantially higher UV-C radiant efficiency than tested luminaires with other designs, potentially cutting energy use by 75%. These results indicate a substantial opportunity for more energy efficient LPM luminaire designs, while demonstrating that UV LED luminaires can offer comparable UV-C radiant efficiency in this application. This may seem surprising, given that LED emitters have lower UV-C radiant efficiency than LPM lamps, but the efficiency-throttling louvers that are generally required for LPM luminaires typically are not needed for LEDs thanks to their directionality. However, lateral beam angles (which describe beam width as viewed from above) were 41–83° for LED luminaires versus 89–110° for LPM luminaires. More luminaires may be required if their lateral beam angles are relatively small, and coverage may be poor if UV-C radiant intensity distribution (i.e., beam shape) is not considered when designing systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

The Demonstration of Power over Ethernet (PoE) Technologies in Commercial and Institutional Buildings

PoE technologies are currently ubiquitous in offices in the form of phones, access points, and IP security cameras and managed by on-site IT staff. As low voltage DC-power capabilities have increased with network switches, PoE devices are now being integrated across additional building systems, including lighting, computers, and HVAC controls. Since PoE devices are connected to network switches, energy monitoring and management can be performed through the IT network management software. Data and results from technology validations are still very limited for PoE equipment. This lack of information hinders higher adoption as its benefits and challenges have been insufficiently quantified in real-world scenarios. The use of IT network switches to power and control lighting, plug loads, and HVAC were demonstrated at a variety of sites including offices, schools, and a hotel. This paper presents the findings of a three-year DOE-/State of Minnesota-funded project that demonstrated and assessed the energy and non-energy benefits of Power over Ethernet (PoE) technologies at four commercial/institutional sites. The goals of the demonstrations were to: (1) assess the receptiveness of commercial and institutional markets to these new technologies, (2) demonstrate the feasibility of PoE technologies within standard design/construction practices and commercial codes, (3) assess the energy and cost savings opportunities of these technologies, (4) provide energy management opportunities where they typically are not available, and (5) formulate approaches to spur adoption of these technologies in the marketplace.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

The Demonstration of Power over Ethernet (PoE) Technologies in Commercial and Institutional Buildings

PoE technologies are currently ubiquitous in offices in the form of phones, access points, and IP security cameras and managed by on-site IT staff. As low voltage DC-power capabilities have increased with network switches, PoE devices are now being integrated across additional building systems, including lighting, computers, and HVAC controls. Since PoE devices are connected to network switches, energy monitoring and management can be performed through the IT network management software. Data and results from technology validations are still very limited for PoE equipment. This lack of information hinders higher adoption as its benefits and challenges have been insufficiently quantified in real-world scenarios. The use of IT network switches to power and control lighting, plug loads, and HVAC were demonstrated at a variety of sites including offices, schools, and a hotel. This paper presents the findings of a three-year DOE-/State of Minnesota-funded project that demonstrated and assessed the energy and non-energy benefits of Power over Ethernet (PoE) technologies at four commercial/institutional sites. The goals of the demonstrations were to: (1) assess the receptiveness of commercial and institutional markets to these new technologies, (2) demonstrate the feasibility of PoE technologies within standard design/construction practices and commercial codes, (3) assess the energy and cost savings opportunities of these technologies, (4) provide energy management opportunities where they typically are not available, and (5) formulate approaches to spur adoption of these technologies in the marketplace.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Sequence-to-sequence neural networks for short-term electrical load forecasting in commercial office buildings

The U.S. power grid is transforming to become smarter, cleaner, and more effi- cient. This is leading to the addition of significant distributed variable renew- able generation. Due to the variable nature of renewable generation, the short- and long-term supply-demand imbalances are less predictable, and conventional approaches to mitigating the imbalance will not be efficient or cost-effective. To address this challenge, transactive control technologies have been proposed which balance energy generation and consumption with market activity and in- frastructural limitations. Transactive control requires the ability of individual end-use loads to express flexibility as a function of a transactive signal (e.g., price). Empirical gray- and black-box models have been widely used to express flexibility, and although these approaches are generally easy to construct and simple to use, they do not capture the non-linear behavior that some end-use loads represent . Machine learning approaches have been proposed to address this limitation. Although deep learning approaches for forecasting end-use loads have been explored, certain aspects of the application of deep models to load forecasting are not well understood. These aspects include how much training data is required, and how models should be structured and trained. To that end, this work explores how to approach applying deep recurrent neural networks to short-term electrical load forecasting with a case study of four commercial office buildings. We identify data requirements for training accurate models of whole building electricity use conditioned on outdoor temperature, provide insight into model hyperparameter sensitivity, and demonstrate how readily models can be generalized to unseen buildings.

Skomski, Elliott↗
DOE OSTI2025

Comparative life cycle assessment of a modular cross-laminated timber residential building designed for disassembly and reuse versus traditional wood frame construction

There is a need for affordable housing across the U.S., with high-performance modular and prefabricated buildings providing a logical avenue for meeting some of this demand. However, there is a need to balance high performance construction – including low emissions – with affordability. To provide a proof-of-concept in meeting these goals, the Circular Home is a cross-laminated timber (CLT)-based deconstructible and reconfigurable single-family residence that meets high performance targets in moisture, energy, design, economics, and life cycle assessment (LCA). This study focuses on the LCA, presenting a cradle-to-cradle whole-building life cycle assessment (WBLCA) for the Circular Home and a functionally equivalent Baseline Home constructed with traditional materials and methods. The functional unit is 1 m 2 of gross floor area across 60 years. Revit building information models (BIM) provided material quantities and Tally LCA was utilized for impact data (inclusive of biogenic carbon sequestration), supplemented with manufacturer environmental product declarations (EPDs). The Circular Home outperforms the baseline residence in most measured impact categories, including global warming potential (GWP), producing −2.73 kgCO 2 eq/m 2 in embodied emissions, whereas the modeled baseline has an embodied GWP of 428 kgCO 2 eq/m 2 . The careful material selection and advanced building design optimizes performance, with the Circular Home containing only −0.006 times the embodied emissions and −0.02 times the operational emissions of its traditional counterpart. Finally, the unique contribution of this work is in the environmental impact comparison of a high-performance modular CLT structure that can be affordably scaled and mass produced in a U.S. market, compared to typical single family home construction.

Circularity↗
DOE OSTI2025

A hybrid surrogate modeling framework for the Digital Twin of a Fluoride-salt-cooled High-temperature Reactor (FHR)

While nuclear energy is a non-greenhouse-gas emitting energy source, expensive operational costs due to the high-level of safety requirements decreases their competitiveness in the sustainable energy market. Advanced reactor concepts paired with Digital Twins aim to increase the commercialization gains of nuclear energy by reducing operational costs, increasing reactor reliability and enhancing power generation. To support Digital Twin tasks such as real-time autonomous control, proactive maintenance monitoring or optimizing power demand operations, a fast and accurate virtual representation of the Nuclear Power Plant (NPP) is required. The computational cost of high-fidelity, physics-based models are unsuitable for real-time analysis or scalability. Here, in this work, a hybrid surrogate modeling framework is developed fora Fluoride-salt-cooled High-temperature Reactor (FHR) that leverages physics-inspired models for key reactor components and uses data-driven methods for rapid system state space prediction. The Xenon reactivity feedback model is integrated to inform the surrogate model about the reactor core and the homologous pump theory model is the basis for representing pump degradation. Using a detailed, two dimensional thermal hydraulics model to generate data on the FHR, we train a network of Vectorized Autoregressive Moving-Average with eXogenous input (VARMAX) models to predict the remaining state values. The result is a surrogate model that provides a detailed reactor state representation of 41 system states and a pump degradation analysis. The framework is applied to Load Follows profiles, yielding high accuracy and a speedup that is more than 4000x faster compared to the higher- fidelity thermal hydraulics model, enabling real-time operational intelligence and applications in long horizon predictions. While the surrogate model framework is demonstrated for the particular case of FHR, the hybrid physical/data-driven modeling approach including the network of surrogates and the underlying modularity has the potential to be applied to other physical asset systems.

Digital Twins↗
DOE OSTI2020

Real-World Evaluation of National Energy Efficiency Potential of Cold Storage Evaporator Technology in the Context of Engine Start-Stop Systems

National concerns over energy consumption and emissions from the transportation sector have prompted regulatory agencies to implement aggressive fuel economy targets for light-duty vehicles through the U.S. National Highway Traffic Safety Administration/Environmental Protection Agency (EPA) Corporate Average Fuel Economy (CAFE) program. Automotive manufacturers have responded by bringing competitive technologies to market that maximize efficiency while meeting or exceeding consumer performance and comfort expectations. In a collaborative effort among Toyota Motor Corporation, Argonne National Laboratory (ANL), and the National Renewable Energy Laboratory (NREL), the real-world savings of one such technology is evaluated. A commercially available Toyota Highlander equipped with two-phase cold storage technology was tested at ANL’s chassis dynamometer testing facility. The cold storage technology maintains the thermal state of air-conditioning evaporators to enable longer and more frequent engine-off operation in vehicles equipped with start-stop functionality. Test results were analyzed and provided to NREL where a novel simulation framework was developed and calibrated to the test data. The vehicle model was then exercised over a large set of real-world drive cycle and ambient condition data to estimate national-level fuel economy benefits. Results indicate that the cold storage evaporator provided national fuel consumption reductions of 0.113% relative to a conventional evaporator in the same vehicle. In addition, when the cold storage evaporator engine stop/start was enabled for any temperature and the baseline was limited to the EPA menu, Start and Stop credit assumption of 27°C, a national fuel savings of 0.497% was found. Fuel savings resulted from a combination of extended engine-off duration during idle events and increased frequency of deceleration fuel cutoff, both enabled by the ability of the cold storage evaporator to maintain thermal state in situations where air conditioning is active.

DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Misuse Detection for a Generalized SFR Test Reactor

Sodium-cooled Fast Reactors (SFRs) present unique challenges for international safeguards. SFRs possess neutron physics characteristics that if configured appropriately could produce more fissile material than consumed. An adversary state may choose to build an SFR, justified by a lack of domestic natural uranium and limited access or interest to procuring uranium from international markets. Once constructed, the state may choose to misuse the SFR for the purpose of diverting fissile plutonium from declared operation. This work shows that a demonstration SFR does not need to be configured as a plutonium breeder to create one Significant Quantity (SQ) of plutonium in a short amount of time (e.g., one to few years). However, such an extreme case of misuse would change the core reactivity in such a way as to be easily indicated by deviations of control rod position compared to declared operation. In this work a contrived SFR demonstration reactor was modeled for the purpose of exploring proliferation scenarios and how such misuse could be detected using the SFR's Reactor Data Acquisition System (RDAS). Typically, the International Atomic Energy Agency (IAEA) does not have access to the control rod position, power, thermal, pressure sensing and indicating systems of nuclear power plants. However, this work shows that such data streams can be compared against a parallel detailed simulation model (a Digital Twin) to detect possible misuse.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2026

LAF-Net: A Deep Residual and Cross-Attention Framework for Day-Ahead Load Forecasting: Preprint

Accurate day-ahead load forecasting is essential for reliable power system operations and market efficiency. System operators such as the Midcontinent Independent System Operator (MISO) rely on forecasts from multiple vendors, yet combining them effectively remains a persistent challenge due to vendor-specific biases. This paper presents a novel LSTM-Attention Fusion Network with Error Representation (LAF-Net) that enhances day-ahead hourly load forecasting through deep residual learning and multi-modal cross-attention. The proposed model builds a historical error memory from past vendor performance and dynamically queries it with future hour context to generate adaptive, hour-specific trust weights for each vendor. A bounded residual correction further refines forecasts by mitigating systematic and temporally localized errors. Tested on real MISO LBA data with multi-vendor forecasts, LAF-Net consistently outperforms the best vendor baseline across all 38 LBAs, achieving more than a 40% reduction in system-level mean absolute error (MAE) during peak load hours relative to the best vendor baseline.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Non-routine adjustments – towards standardizing M&V approach for quantifying the effects of static factors

The success of an energy management program relies on ensuring that the energy savings can be verified with an adequate level of certainty. Energy savings cannot be directly measured and hence have to be deduced by comparing the pre-retrofit energy consumption with post-retrofit energy consumption data adjusted to account for differences in conditions. These adjustments are needed, since conditions that influence energy consumption may not stay the same between pre- and postinstallation phase of the project. These adjustments can often be routine when accounting for factors like production volume and weather that are expected to change and are included in the energy consumption adjustment model. Existing measurement and verification (M&V) resources and guidance mostly concentrate on developing models for routine adjustment of one or more factors that normally change. On the other hand, there are factors (static) like product mix, operating hours, gross square area, etc. that are assumed to stay constant during normal conditions. However, in order to adapt to dynamic market conditions, the industries are forced to react thereby leading to changes to these static factors. Identifying these static factors that warrant adjustment, called non-routine event, along with quantifying their effect on energy consumption can be complex and lack of proper guidance can exacerbate this issue. This paper reviews some of the current work in terms of how non-routine events are defined, characterized, detected and quantified based on a review of existing M&V guidelines, protocols and other relevant literature. This work also reviewed some of the existing non-routine events and adjustment practices to understand how these different aspects are addressed along with a discussion on some of the key challenges and gaps in the current guidance.

Earni, Shankar↗
NASA NTRS2010

A GPS-Based Pitot-Static Calibration Method Using Global Output-Error Optimization

Pressure-based airspeed and altitude measurements for aircraft typically require calibration of the installed system to account for pressure sensing errors such as those due to local flow field effects. In some cases, calibration is used to meet requirements such as those specified in Federal Aviation Regulation Part 25. Several methods are used for in-flight pitot-static calibration including tower fly-by, pacer aircraft, and trailing cone methods. In the 1990 s, the introduction of satellite-based positioning systems to the civilian market enabled new inflight calibration methods based on accurate ground speed measurements provided by Global Positioning Systems (GPS). Use of GPS for airspeed calibration has many advantages such as accuracy, ease of portability (e.g. hand-held) and the flexibility of operating in airspace without the limitations of test range boundaries or ground telemetry support. The current research was motivated by the need for a rapid and statistically accurate method for in-flight calibration of pitot-static systems for remotely piloted, dynamically-scaled research aircraft. Current calibration methods were deemed not practical for this application because of confined test range size and limited flight time available for each sortie. A method was developed that uses high data rate measurements of static and total pressure, and GPSbased ground speed measurements to compute the pressure errors over a range of airspeed. The novel application of this approach is the use of system identification methods that rapidly compute optimal pressure error models with defined confidence intervals in nearreal time. This method has been demonstrated in flight tests and has shown 2- bounds of approximately 0.2 kts with an order of magnitude reduction in test time over other methods. As part of this experiment, a unique database of wind measurements was acquired concurrently with the flight experiments, for the purpose of experimental validation of the optimization method. This paper describes the GPS-based pitot-static calibration method developed for the AirSTAR research test-bed operated as part of the Integrated Resilient Aircraft Controls (IRAC) project in the NASA Aviation Safety Program (AvSP). A description of the method will be provided and results from recent flight tests will be shown to illustrate the performance and advantages of this approach. Discussion of maneuver requirements and data reduction will be included as well as potential applications.

Foster, John V.↗
NASA NTRS2017

Airborne Trajectory Management (ABTM): A Blueprint for Greater Autonomy in Air Traffic Management

The aviation users of the National Airspace System (NAS) - the airlines, General Aviation (GA), the military and, most recently, operators of Unmanned Aircraft Systems (UAS) - are constrained in their operations by the design of the current paradigm for air traffic control (ATC). Some of these constraints include ATC preferred routes, departure fix restrictions and airspace ground delay programs. As a result, most flights cannot operate on their most efficient business trajectories and a great many flights are delayed even getting into the air, which imposes a significant challenge to maintaining efficient flight and network operations. Rather than accepting ever more sophisticated scheduling solutions to accommodate the existing constraints in the airspace, a series of increasingly capable airborne technologies, integrated with planned improvements in the ground system through the Federal Aviation Administration (FAA) Next Generation Air Traffic Management System (NextGen) programs, could produce much greater operational flexibility for flight path optimization by the aviation system users. These capabilities, described in research coming out of NASA's Aeronautics Research Mission Directorate, can maintain or improve operational safety while taking advantage of air and ground NextGen technologies in novel ways. The underlying premise is that the nation's physical airspace is still abundant and underused, and that the delays and inefficient flight operations resulting from artificial structure in airspace use and procedural constraints on those operations may not be necessary for safe and efficient flight. This article is not an indictment of today's NAS or the people who run it. Indeed, it is an exceptional achievement that Air Traffic Management (ATM) - the complex human/machine conglomeration of communications, navigation and surveillance equipment and the rules and procedures for controlling traffic in the airspace - has both the capacity and enables the degree of efficiency in air travel that it does. But it is also true that sixty years of the "radar religion" (i.e., reliance on radar-based command and control) has produced several generations of ATM system operators and researchers who believe that introducing automation within the existing functional structure of ATM is the only way to "modernize" the system. Even NextGen, which began as a proposal for "transformational" change in the way ATC is performed, has morphed over the last decade and a half to become just the inclusion of Global Positioning System (GPS) for navigation, Automatic Dependent Surveillance Broadcast (ADS-B) for surveillance, and Data Communications (Data Comm) for communications, while still operating in rigidly structured airspace with human controllers being responsible for separation and traffic flow management (TFM) within defined sectors of airspace, using the same horizontal separation standards that have been in use since raw primary radar was introduced in the 1950s. No system as massive as the current NAS ATM can be replaced with a better system while simultaneously meeting the transportation and other aviation needs of the nation. A new generation of more flexible operations must emerge and yet coexist in harmony with the current operation (i.e., share the same airspace without segregation), thereby enabling a long-term transformation to take place in the way increasing numbers of flights are handled. Market forces will be the ultimate driver of this transformation, and investment realities mandate that real benefits must accrue to the first operators to adopt these new capabilities. In fact, the kinds of missions envisioned in the emerging world of UAS operations, unachievable under conventional ATM, demand that this transformation take place. Airborne Trajectory Management (ABTM) is proposed as a series of transformational steps leading to vastly increased flexibility in flight operations and capacity in the airspace to accommodate many varied airspace uses while improving safety. As will be described, ABTM enables the gradual emergence of a new paradigm for user-based trajectory management in ATM that brings tangible benefits to equipped operators at every step while leveraging the air and ground investments of NextGen. There are five steps in this ABTM transformation.1 NASA has extensively studied the first and last of these steps, and a roadmap of increasing capabilities and benefits is proposed for bridging between these operational concepts.

Cotton, William B.↗
DOE OSTI2020

Medium- and Heavy-Duty Vehicle Electrification: An Assessment of Technology and Knowledge Gaps

The objective of this assessment was to leverage current medium- and heavy-duty vehicle (MHDV) data and information to evaluate the state of commercial vehicle electrification technologies, including the following: 1. Assessment and inventory of current MHDV electrification architectures; 2. Identification and assessment of MHDV component technologies; 3. Assessment of potential performance and cost drivers; and, 4. Identification of R&D gaps where appropriate R&D and technology would accelerate commercial vehicle electrification. These gaps include shortfalls in technology, gaps in data, and inadequate knowledge and understanding. To inform this study, the National Renewable Energy Laboratory–Oak Ridge National Laboratory team examined the open literature; conducted workshops; assessed and analyzed data on more than 175 electrified MHDVs, including vehicle and powertrain specifications; and conducted one-on-one meetings with industry representatives. This systems-level information was concatenated and parsed with respect to key characteristics such as battery energy, power, and range compared across vehicle classes. Operational data of many conventional vehicles were also examined to help determine the requirements on electrified vehicle attributes such as range. Previous studies on the total cost of ownership of electrified MHDVs were reviewed to determine where improvements in technologies (efficiency, cost, maintenance) were needed to accelerate adoption. The team also assessed the state of the art in electric drivetrains for component specifications and challenges for the commercial vehicle sector, including electric machines, power electronics, and off-board high-power charging systems (extreme fast charging and beyond). The goal of this analysis was to identify the barriers to widespread adoption of commercial vehicle electrification technologies and prioritize the research and development gaps that need to be overcome to accelerate significant market penetration of these technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Smart Monitoring and Diagnostic System (SMDS) for Packaged Air Conditioners and Heat Pumps for Small/Medium Commercial Buildings: Preparation for Commercialization: CRADA 478 [Abstract only]

This project will enable Pacific Northwest National Laboratory (PNNL) and industry partner, mCloud Technologies, to work collaboratively to ready the Smart Monitoring and Diagnostic System (SMDS) for commercial deployment and validate its performance under real-world conditions at field sites. This project will specifically focus on 1) implementing the SMDS algorithms in a scalable cloud-based software architecture, 2) designing new, innovative, complimentary commercial services based on the SMDS, 3) enhancing the SMDS energy and cost impact algorithms to reduce uncertainty in estimates, 4) determining the lower limits on SMDS performance degradation detection, 5) validating algorithm performance and default values of adjustable thresholds with existing data from controlled physical testing and from customer packaged air conditioners and heat pumps (commonly referred to as rooftop units or RTUs), 6) field testing to validate the system on multiple customer buildings in diverse environments, and 7) expanding field deployment to a larger set of mCloud’s customer buildings. Project results by validating, enhancing, and quantifying the performance of the SMDS will position mCloud, and potential future licensees, to implement the SMDS in commercial offerings that encourage and enable use of condition-based and predictive maintenance, leading to significant reductions in energy use and greenhouse gas emissions associated with space conditioning by RTUs. Furthermore, these enhancements will increase the value of the SMDS for users and increase the potential market for its use and impacts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Numerical analysis of soot emissions from gasoline-ethanol and gasoline-butanol blends under gasoline compression ignition conditions

In the present work, computational fluid dynamics (CFD) simulations of a single-cylinder gasoline compression ignition (GCI) engine were performed to investigate the impact of blending two biofuels, ethanol and n-butanol, with gasoline on the trade-off between combustion phasing and soot emissions under low load conditions. Here, in order to represent market gasoline (RD5-87), a four-component toluene primary reference fuel (TPRF) + ethanol (ETPRF) surrogate (with 20% ethanol by mole; E20) was formulated using a neural network based octane predictor such that the surrogate had the same ethanol content, Research Octane Number (RON) and Octane Sensitivity (S). In addition, a novel skeletal kinetic mechanism for ETPRF and TPRF + n-butanol (BTPRF) blends, incorporating polycyclic aromatic hydrocarbon (PAH) chemistry, was developed. A three-dimensional (3D) engine CFD formulation employing the skeletal mechanism, adaptive mesh refinement (AMR), finite-rate chemistry approach, and hybrid method of moments (HMOM) was adopted to capture the in-cylinder combustion phenomena and soot emissions. The engine CFD model was validated against RD5-87 experimental data for a broad range of start-of-injection (SOI) timings (-21/-27/-36/-45 crank angle degrees (CAD) after top-dead center (aTDC)), with respect to in-cylinder pressure, heat release rate, combustion phasing, and soot emissions. The closed-cycle simulation results were analyzed to elucidate the non-monotonic trend of soot emissions versus SOI timing: SOI-36 > SOI-45 > SOI-21 > SOI-27. Thereafter, the validated CFD model was employed to simulate the combustion of a gasoline-ethanol blend with 45% (by mole) ethanol (E45) and a gasoline-butanol blend with 45% (by mole) n-butanol (B45) under the same operating conditions to study the effects of fuel composition and SOI timing on combustion phasing and soot emissions. The sooting propensity followed the trend: B45 > E20 > E45 at all SOI timings. Overall, it was observed that the autoignition propensity was primarily related to fuel chemistry. On the other hand, sooting propensity showed strong coupling with both fuel chemistry and physical properties, with greater impact of fuel physical properties at advanced SOI timings.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Site-specific Design Case Study for Wet Waste Hydrothermal Liquefaction and Biocrude Upgrading to Hydrocarbon Fuels

Hydrothermal liquefaction (HTL) is a thermal process that converts wet biomass to renewable hydrocarbon fuel blendstocks (i.e., renewable naphtha, renewable diesel, and sustainable aviation fuel (SAF)). It can utilize a wide range of pure and blended wet feedstocks, including sewage sludge from water resource recovery facilities (WRRF), food and agriculture wastes, algae, fats, oils and greases (FOG) and blends of dry and wet wastes/feedstocks. Historically, techno-economic analysis (TEA) and annual state of technology (SOT) assessments with standard economic assumptions used by the Bioenergy Technologies Office (BETO) were conducted for the wet waste HTL pathway leveraging experimental data collected from Pacific Northwest National Laboratory’s (PNNL) continuous flow reactor systems. The objective of the SOT assessment has been to guide and track progress of BETO’s HTL research and development (R&D) toward reduced cost and greenhouse gas (GHG) emissions for the pathway. However, gaps exist between BETO’s traditional SOT updates and the needs of key external stakeholders that – if addressed – will accelerate technology adoption. This Business Case Study aims to bridge this gap by providing an updated design, TEA, and LCA based on PNNL’s FY23 R&D with added analyses and information that provide enhanced relevance for stakeholders of the HTL technology. This includes specific siting, regional wet waste resource inventory and transportation cost analyses, fuel market information, sustainable fuel policy impacts, economic metrics of net present value (NPV) and internal rate of return (IRR), greenhouse gas (GHG) emissions analysis, and statistical analysis of cost and technical uncertainties of the HTL plant design. The study focuses on the “Detroit combined statistical area (CSA)” region for siting of a wet waste HTL plant adjacent to the Great Lakes Water Authority (GLWA) facility with guidance from industry participants. Regional resource and siting analyses were conducted to identify feedstock availability, scale, and cost, as well as a beneficial site location. TEA with detailed rigorous capital cost estimation for the specific site application was conducted to evaluate the key economic metrics of most value to industrial partners. These include total capital investment, operating costs, minimum fuel selling price (MFSP) of the biocrude and fuel blendstock, and NPV and internal rate of return IRR with sustainable fuel credits. Life cycle analysis was conducted to evaluate the supply chain greenhouse gas (GHG) emissions for the wet waste HTL process as compared with petroleum derived diesel. This study is also informed by years of R&D and process de-risking learnings and was conducted with a basic engineering HTL plant design and costing that akin to a “first-of-a-kind” plant economics. This differs from our conventional “nth plant ” SOT assessments. Specifically, the HTL process model has been updated with more operationally reliable methods for feed heating and phase separations. Further, we have implemented additional spare equipment for redundancy, a more rigorous installed equipment cost estimation approach, and additional costs associated with feed formatting and delivery, building, piping and site development. An Excel-based cost sheet based on the basic engineering design is also released alongside the report that allows users to conduct customized TEA with their own feed composition and financial assumptions.

09 BIOMASS FUELS↗
DOE OSTI2024

Supporting data for Site-specific Design Case Study for Wet Waste Hydrothermal Liquefaction and Biocrude Upgrading to Hydrocarbon Fuels

Hydrothermal liquefaction (HTL) is a thermal process that converts wet biomass to renewable hydrocarbon fuel blendstocks (i.e., renewable naphtha, renewable diesel, and sustainable aviation fuel (SAF)). It can utilize a wide range of pure and blended wet feedstocks, including sewage sludge from water resource recovery facilities (WRRF), food and agriculture wastes, algae, fats, oils and greases (FOG) and blends of dry and wet wastes/feedstocks. Historically, techno-economic analysis (TEA) and annual state of technology (SOT) assessments with standard economic assumptions used by the Bioenergy Technologies Office (BETO) were conducted for the wet waste HTL pathway leveraging experimental data collected from Pacific Northwest National Laboratory’s (PNNL) continuous flow reactor systems. The objective of the SOT assessment has been to guide and track progress of BETO’s HTL research and development (R&D) toward reduced cost and greenhouse gas (GHG) emissions for the pathway. However, gaps exist between BETO’s traditional SOT updates and the needs of key external stakeholders that – if addressed – will accelerate technology adoption. This Business Case Study aims to bridge this gap by providing an updated design, TEA, and LCA based on PNNL’s FY23 R&D with added analyses and information that provide enhanced relevance for stakeholders of the HTL technology. This includes specific siting, regional wet waste resource inventory and transportation cost analyses, fuel market information, sustainable fuel policy impacts, economic metrics of net present value (NPV) and internal rate of return (IRR), greenhouse gas (GHG) emissions analysis, and statistical analysis of cost and technical uncertainties of the HTL plant design. The study focuses on the “Detroit combined statistical area (CSA)” region for siting of a wet waste HTL plant adjacent to the Great Lakes Water Authority (GLWA) facility with guidance from industry participants. Regional resource and siting analyses were conducted to identify feedstock availability, scale, and cost, as well as a beneficial site location. TEA with detailed rigorous capital cost estimation for the specific site application was conducted to evaluate the key economic metrics of most value to industrial partners. These include total capital investment, operating costs, minimum fuel selling price (MFSP) of the biocrude and fuel blendstock, and NPV and internal rate of return IRR with sustainable fuel credits. Life cycle analysis was conducted to evaluate the supply chain greenhouse gas (GHG) emissions for the wet waste HTL process as compared with petroleum derived diesel. This study is also informed by years of R&D and process de-risking learnings and was conducted with a basic engineering HTL plant design and costing that akin to a “first-of-a-kind” plant economics. This differs from our conventional “nth plant ” SOT assessments. Specifically, the HTL process model has been updated with more operationally reliable methods for feed heating and phase separations. Further, we have implemented additional spare equipment for redundancy, a more rigorous installed equipment cost estimation approach, and additional costs associated with feed formatting and delivery, building, piping and site development. An Excel-based cost sheet based on the basic engineering design is also released alongside the report that allows users to conduct customized TEA with their own feed composition and financial assumptions.

Li, Shuyun↗
NASA NTRS1997

Carbon in the Former Soviet Union: The Current Balance

This work has been carried out in a period of great changes in Russia that have brought extreme hardships to the scientific community. We have been fortunate in establishing excellent relationships with the Russian scientific community and believe we have helped to retain coherence in circumstances where the continuation of research was in doubt. We have learned much and have been effective in advancing, even establishing, scholars and programs in Russia that might not otherwise have survived the transition. The vigor of the International Boreal Forest Research Association (IBFRA) is one sign of the value and success of these activities. Largely due to the current political and economic transitions in the former Soviet Union, the forests of much of the FSU are under reduced logging pressure. In addition, there is a decline in air pollution as heavy industry has waned, at least for now. Russian forestry statistics and our personal experience indicate a decline, perhaps as high as 60%, in forest harvesting over the last few years. But, new international market pressures on the forests exist in European Russia and in the Far East. The central government, still the "owner" of Russian forests, is having difficulty maintaining control over forest use and management particularly in the Far East and among the southern territories that have large, nonRussian ethnic populations. Extraordinarily large areas of mixed forest and grasslands, sparse or open forests, and mixed forests and tundra must be considered when calculating forest area It is insufficient to think of Russia as simply forest and nonforest Forest productivity, measured as growth of timber, appears to be in decline in all areas of Russia except in European Russia. Most information and publications on the recent history of these forests is heavily dependent on statistical data from the Soviet era. The interpretation of these data is very much open to debate. Anatoly Shwidenko, a long term collaborator and former senior scientist (mensuration) for the Soviet Committee on Forests, now a scholar at the International Institute of Applied Systems Analysis (IIASA), Vienna, has provided abundant contributions from the data available to him and from his experience. Forest stand carbon is concentrated in the Russian Far East (i.e. Primorski Kray), Central-Southern Siberia and European Russia But, soil carbon can be 10 times forest stand C. Our efforts in mapping the area and changes in area (as well as the internal structure) of forests have made major contributions to our joint understanding of the scale and status of these forests. To realize the importance of this contribution one needs only to recognize that any large scale Soviet-era maps of the area did not include latitude and longitude. Even today, there is great reluctance to provide these data, the basis of any GIS.

Woodwell, G. M.↗