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DOE OSTI2024

Search for beyond-mean-field signatures in heavy-ion fusion reactions

Examination of high-resolution, experimental fusion excitation functions for 16,17,18 O + 12 C reveals a remarkable irregular behavior that is rooted in the structure of both the colliding nuclei and the quasi-molecular composite system. The impact of the l-dependent fusion barriers is assessed using a time-dependent Hartree-Fock model, viewed as a mean-field reference. Barrier penetrabilities, taken directly from a density-constrained calculation, provide a significantly improved description of the experimental data as compared to the standard Hill-Wheeler approach. Furthermore, the remaining deviations between the parameter-free theoretical mean-field predictions and experimental fusion cross sections are exposed and discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Directional Laplacian Centrality for Cyber Situational Awareness

Cyber operations is drowning in diverse, high-volume, multi-source data. To get a full picture of current operations and identify malicious events and actors, analysts must see through data generated by a mix of human activity and benign automated processes. Although many monitoring and alert systems exist, they typically use signature-based detection methods. We introduce a general method rooted in spectral graph theory to discover patterns and anomalies without a priori knowledge of signatures. We derive and propose a new graph-theoretic centrality measure based on the derivative of the graph Laplacian matrix in the direction of a vertex. To build intuition about our measure, we show how it identifies the most central vertices in standard network datasets and compare to other graph centrality measures. Finally, we focus our attention on studying its effectiveness in identifying important IP addresses in network flow data. Using both real and synthetic network flow data, we conduct several experiments to test our measure’s sensitivity to two types of injected attack profiles and show that vertices participating in injected attack profiles exhibit noticeable changes in our centrality measures, even when the injected anomalies are relatively small, and in the presence of simulated network dynamics.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2024

RhizoNet: semantic segmentation of plant roots using CNN (RhizoNet) v0.0.1

RhizoNet is designed for the semantic segmentation of plant root scans, utilizing a sophisticated deep learning network known as Residual Unet. It specializes in processing color images of plants cultivated in a hydroponic EcoFAB system, captured using an Epson scanner. The core of the algorithm is based on Residual U-nets, which significantly improve prediction accuracy. This is achieved through the implementation of a convex hull operation, which effectively delineates the primary root component by leveraging spatio-temporal image data. This enables researchers to accurately assess predicted biomass and monitor plant growth over time.

Ushizima, Daniela↗

DOE OSTI2025

Agricultural Management Legacy Effects on Switchgrass Growth and Soil Carbon Gains

Switchgrass ( Panicum virgatum L.) is a native North American grass currently considered a high-potential bioenergy feedstock crop. However, previous reports questioned its effectiveness in generating soil organic carbon (SOC) gains, with resultant uncertainty regarding the monoculture switchgrass's impact on the environmental sustainability of bioenergy agriculture. We hypothesize that the inconsistencies in past SOC accrual results might be due, in part, to differences in prior land management among the systems subsequently planted to switchgrass. To test this hypothesis, we measured SOC and other soil properties, root biomass, and switchgrass growth in an experimental site with a 30-year history of contrasting tillage and N-fertilization treatments, 7 years after switchgrass establishment. We determined switchgrass' monthly gross primary production (GPP) for six consecutive years and conducted deep soil sampling. Nitrogen fertilization expectedly stimulated switchgrass growth; however, a tendency for better plant growth was also observed under unfertilized settings in the former no-till soil. In topsoil, SOC significantly increased from 2007 to 2023 in fertilized treatments of both tillage histories, with the greatest increase observed in fertilized no-till. Fertilized no-till also had the highest particulate organic matter content in the topsoil, with no differences among the treatments observed in deeper soil layers. However, regardless of fertilization, the tillage history had a strong effect on stratification with depth of SOC, total N, and microbial biomass C. Results suggested that historic and ongoing N fertilization had a substantial impact on switchgrass growth and soil characteristics, while tillage legacy had a much weaker, but still discernible, effect.

bioenergy crop production system↗

DOE OSTI2024

Maximizing energy efficiency in wastewater treatment plants: A data-driven approach for waste heat recovery and an economic analysis using Organic Rankine Cycle and thermal energy storage

Maximizing energy efficiency through waste heat recovery (WHR) processes is crucial for sustainable and ecofriendly operations across multiple industries, notably in wastewater treatment plants (WWTPs). This work proposes a comprehensive approach for assessing the WHR feasibility in WWTPs, structured in two main objectives. Firstly, an Artificial Neural Network (ANN) model is developed to accurately predict WHR based on operational data, including biogas temperature, biogas pressure, daily production in kWh, and WHR values in kWh th . The second objective focuses on economically evaluating the WHR feasibility based on the estimated WHR values obtained by the ANN model, and then realistically assessing the economic feasibility of integrating the Organic Rankine Cycle (ORC) and Seasonal Thermal Energy Storage (STES) systems. With an application to the As-Samra WWTP located in Jordan, the developed ANN model demonstrates promising results in the validation phase, with a root mean square error (RMSE) of 2206 kWh/day, a mean absolute error (MAE) of 1674 kWh/day, and an R-squared (R 2 ) value of 68%. On the other hand, the economic analysis reveals that an optimal ORC system of 412.14 kW e capacity yields a Net Present Value (NPV) of 2.09 million US dollars, a Levelized Cost of Energy (LCOE) of 0.0749 USD/kWh, a Payback Period (PBP) of 4.8 years, and annual revenues of 428 kUSD. This work also investigates the techno-economic feasibility of integrating ORC-STES. Results indicate that the LCOE and PBP are highly affected by the ORC's capital cost, and integrating STES increases the LCOE to 0.0824 USD/kWh, rendering its integration with ORC infeasible. In conclusion, this study aims to advance the understanding and application of WHR in WWTPs, paving the way for more efficient and sustainable practices in the field.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Serendipita Fungi Modulate the Switchgrass Root Transcriptome to Circumvent Host Defenses and Establish a Symbiotic Relationship

The fungal family Serendipitaceae encompasses root-associated lineages with endophytic, ericoid, orchid, and ectomycorrhizal lifestyles. Switchgrass is an important bioenergy crop for cellulosic ethanol production owing to high biomass production on marginal soils otherwise unfit for food crop cultivation. The aim of this study was to investigate the host plant responses to Serendipita spp. colonization by characterizing the switchgrass root transcriptome during different stages of symbiosis in vitro. For this, we included a native switchgrass strain, Serendipita bescii, and a related strain, S. vermifera, isolated from Australian orchids. Serendipita colonization progresses from thin hyphae that grow between root cells to, finally, the production of large, bulbous hyphae that fill root cells during the later stages of colonization. We report that switchgrass seems to perceive both fungi prior to physical contact, leading to the activation of chemical and structural defense responses and putative host disease resistance genes. Subsequently, the host defense system appears to be quenched and carbohydrate metabolism adjusted, potentially to accommodate the fungal symbiont. In addition, prior to contact, switchgrass exhibited significant increases in root hair density and root surface area. Furthermore, genes involved in phytohormone metabolism such as gibberellin, jasmonic acid, and salicylic acid were activated during different stages of colonization. Both fungal strains induced plant gene expression in a similar manner, indicating a conserved plant response to members of this fungal order. Understanding plant responsiveness to Serendipita spp. will inform our efforts to integrate them into forages and row crops for optimal plant–microbe functioning, thus facilitating low-input, sustainable agricultural practices.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Experiments on a vapor compression air conditioner with liquid desiccants for efficient dehumidification

Buildings require air conditioning systems that not only cool and dehumidify supply air but also provide sufficient ventilation to ensure indoor air quality and occupant comfort. However, standard recirculation systems-which introduce about a 10 % to 20 % fraction of outdoor air-often fail to deliver air that is precisely cooled and dry, particularly because 80-90 % of the ventilation cooling load is latent. Mixing humid ventilation air with recirculated indoor air increases the energy and costs required to condition the air to comfortable levels. Dedicated outdoor air systems (DOASs) are designed to handle this latent dominated ventilation load and thus need to have efficient humidity removal. Many cooling cycles can perform this task. Here we describe a liquid desiccant DOAS, which combines a vapor compression cycle and a liquid desiccant absorber and desorber pair. We present its performance at 26 operating conditions and a thermodynamic model which can accurately predict the moisture removal efficiency. The model's performance predictions have a mean percentage error of 2.5 % and a coefficient of variation of the root mean square error of 7.5 %. We also compare the performance of this vapor-compression-coupled liquid desiccant system with a standard vapor compression system with the same components but no liquid desiccant. For the 26 conditions tested in this study, this comparison shows that adding liquid desiccants lowers the required evaporator cooling load by 21 %, allows for 25 % lower compressor volumetric capacity, and 25 % lower electricity use. Future work will leverage this model to quantify the reduction in annual electricity use across different climates, including the need for a standard vapor compression system to reheat the air during some of the year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Recommendations for Minimum Required Diagnostics Information for Electric Vehicle Charging Infrastructure

The rapid growth of electrified transportation, including light- and medium-duty electric vehicles (EVs) as a mobility solution requires a reliable EV charging infrastructure. To advance charging reliability, the ChargeX Consortium reports “Recommendations for Minimum Required Error Codes for Electric Vehicle Charging Infrastructure” and “Implementation Guide for Minimum Required Error Codes in Electric Vehicle Charging Infrastructure” have provided recommendations for a set of minimum required error codes (MRECs), their functional and responsibility classifications, and a guide for their implementation using OCPP versions 1.6J and 2.0.1. These reports outline a recommended practice for consistent error reporting and interpretation, which is essential for communicating issues uniformly across the complex and diverse EV charging ecosystem. However, MRECs are just one part of diagnosing issues, another critical part is obtaining enough information about the current state and performance of the various charging components to identify root causes for each of the error codes. This additional diagnostics data can be used by technicians or automated systems to understand the context around an issue, allowing for timely resolution, decreased maintenance costs, and increased charging reliability. During everyday operations, data is regularly collected and analyzed across the ecosystem. Although sharing of all that available data would be great for diagnostics, concerns on data ownership, privacy, and OEM intellectual property pose a challenge. To overcome this obstacle, this report proposes a set of Minimum Required Diagnostic Information (MRDI) and recommends that the industry implement these uniformly across the North American EV charging ecosystem. MRDI provides a means to exchange only data deemed necessary for root cause determination.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗

DOE OSTI2024

RESOLVING THE ELECTROCHEMICAL EQUATIONS OF A SOLID OXIDE FUEL CELL FOR USE IN TRANSIENT SIMULATION AND INTEGRATION INTO CYBER-PHYSICAL SYSTEMS

A major challenge with complex cyber-physical systems stems from long model computational time that creates a mismatch between the model system and the physical system. The numerical modeling of solid oxide fuel cells (SOFCs) presents particular challenges due to the highly coupled nature of the underlying equations and the multiphysics needed to fully resolve their behavior during a transient event. To this end current approaches revolve around splitting the computational efforts into resolving temperature effects and resolving electrochemical effects. Current methods employed for the transient simulation of an SOFC for implementation in the Hybrid Performance (HyPer) facility cyberphysical plant at the National Energy Technology Laboratory reveal a distinct need for accelerated results with a high degree of stability. To this aim, an investigation into the computational time for the code reveals that the underlying electrochemical algorithm takes an order of magnitude more time than its thermal counterpart and has a tendency to vary in terms of iteration time and as such a rework of the underlying system is proposed. The primary method for accelerated electrochemical algorithm solutions is to employ higher order root finding recipes for the resolution of the highly coupled electrochemical equations. This is done with the intention to reduce the overall number of subiterations necessary for resolving voltage, current density, and species concentration, properties of the fuel cell that are all directly coupled and require nested iterative approaches. The overall objective of this approach is an order of magnitude reduction in calculation time without sacrificing stability and increasing accuracy. Specific approaches involve using both bounded and unbounded techniques, such as the False Position method and the Secant method (or if applicable Newton-Raphson) respectively, the drawbacks being slower convergence for False Position and instability for the Secant or Newton-Raphson methods. Current preliminary results on simplified versions of the parent functions involved for electrochemical calculations indicate a reduction in computational steps by a factor of two for the secant method and a factor of three for Newton-Raphson. When implemented into new modified electrochemical algorithms, the results indicate a possible order of magnitude reduction in calculation time.

Arias, Jesus↗

DOE OSTI2025

Multi-scale dynamic modeling and validation of radial flow fixed bed contactors for post-combustion CO 2 capture using bench scale and pilot plant data

Here, in this work, a multi-scale model of a radial flow fixed bed contactor packed with a carbon sorbent is developed and validated with laboratory-scale and pilot plant scale dynamic data. For the lab scale system, the model results were compared with low, medium and high gas and sweep flowrates, yielding root mean square error (RMSE) of 0.80, 0.63, 0.96 CO 2 mol%, respectively, for the outlet CO 2 concentration profile considering the entire A-D cycle. For the bed outer temperature profile, maximum RMSE was found to be 5.5 °C considering all flowrates and entire A-D cycles. An experimental campaign was developed and applied to a pilot plant at Technology Center Mongstad (TCM), Norway. Approaches were developed for pre-processing of data including consideration of the effect of gas mixing, measurement delay, and determination of cyclic steady-state conditions. Considering profiles during A-D cycles for all test runs, it was found that the maximum RMSE for pressure drop, temperature for the outer section of the bed, temperature for the middle section of the bed, and outlet CO 2 concentration profile remained less than 1.5 mbar, 3.5 °C, 2.8 °C, and 1.3 CO 2 mol%, respectively. The validated model was used to perform sensitivity studies on several key design operating variables for the adsorption-desorption cycle. It was found that the flow rate and concentration of flue gas have dominant nonlinear effects on the breakthrough time while the desorption time was strongly affected by the sweep gas flowrate for the specific sorbent being evaluated in this study.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2021

The PRad windowless gas flow target

In this work, we report on a windowless, high-density, gas flow target at Jefferson Lab that was used to measure $r_p$, the root-mean-square charge radius of the proton. To our knowledge, this is the first such system used in a fixed-target experiment at a (non-storage ring) electron accelerator. The target achieved its design goal of an areal density of 2$\times$10$^{18}$ atoms/cm$^2$, with the gas uniformly distributed over the 4 cm length of the cell and less than 1% residual gas outside the cell. This design eliminated scattering from the end caps of the target cell, a problem endemic to previous measurements of the proton charge radius in electron scattering experiments, and permitted a precise, model-independent extraction of $r_p$ by reaching unprecedentedly low values of $Q^2$, the square of the electron's transfer of four-momentum to the proton.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Spatially resolved fibre cavity ring down spectroscopy

Abstract This paper presents a fibre cavity ring down spectroscopy probed by Rayleigh scattering optical frequency domain reflectometry (OFDR), which provides spatial location of stimuli and improved signal to noise ratio for distributed sensing measurements. A section of optical fibre was integrated into an active fibre ring cavity with optical gain and interrogated by the OFDR system for 11 cycles with a single laser scan. Through the cavity ring down configuration, root-mean-squared (RMS) noise of distributed temperature and strain measurements was reduced to 6.9 mK and less than 0.1 με, respectively for 1-cm spatially resolved measurements. Our work shows that the active fibre cavity configuration can be combined with distributed fibre sensing schemes to achieve both high spatial resolution and high sensitivity measurements.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Arctic shrub expansion generates regional variation in litter decomposition by altering litter quality and the decomposition environment

Abstract The expansion of deciduous shrubs into the graminoid‐dominated arctic tundra is expected to alter litter decomposition by changing litter quality and local abiotic and biotic conditions. However, it remains unclear how shrub expansion will affect litter decomposition at regional scales, where macroclimate is expected to be the dominant regulator of decomposition. To determine the relative influence of macroclimate and local controls on regional patterns of litter mass loss and nitrogen release, we conducted two hierarchical litter decomposition experiments across spatial scales. We decomposed leaf and root litter from a prominent graminoid ( Eriophorum vaginatum ) and three genera of deciduous shrubs ( Betula , Alnus and Salix ) for 1 year within replicated plots at five sites spanning a 160 km latitudinal gradient in northern Alaska. Using Eriophorum litter as a substrate, we found that macroclimate was the primary regulator of mass loss but had opposing effects on leaf and root litter. As summer temperature increased along the latitudinal gradient (11.9 to 13.9°C), leaf litter mass loss increased by 20% whereas root litter mass loss decreased by 33%. Leaf nitrogen release also increased with summer temperature. Conversely, root nitrogen release was controlled by the vegetation type of the decomposition environment. Using different shrub litters as substrates, we found that litter quality and its interaction with soil microclimate and macroclimate controlled decomposition. Overall, shrub root litters decomposed faster than Eriophorum root litter, losing 53% more mass and 190% more nitrogen across all sites and decomposition environments. For leaf litter, however, patterns varied by litter genus, with Salix losing more mass and Betula and Alnus losing less mass than Eriophorum . Our findings demonstrate that shrub expansion in the Arctic can regulate leaf and root litter decomposition at the regional scale through its effects on local controls, primarily litter quality. Ongoing increases in shrub cover are likely to accelerate the turnover of root litter carbon and nitrogen pools in tundra ecosystems. Therefore, including shrub‐related processes in Earth system models will improve our ability to predict regional‐scale litter decomposition and its effects on carbon and nutrient cycling in a warming Arctic. Read the free Plain Language Summary for this article on the Journal blog.

Vozzo, Justin T. [Department of Natural Resources ↗

DOE OSTI2024

Instrumentation for the Investigation of Pitch Bearing Design and Reliability

Recently, there has been an increasing level of industry interest in pitch system and pitch bearing reliability. Pitch bearings are used in wind turbines to connect the blade root to the hub. Some populations of pitch bearings have demonstrated a 12% failure rate in 20 years. As rotor diameters continue to increase for tall land-based and offshore wind turbines, pitch bearings are becoming even larger in diameter, which can make them vulnerable to deflections and consequent stress concentrations. There is an increased need to more accurately study pitch bearing deformations, misalignment, load distributions, and contact stresses. A significant body of work has investigated fatigue lives and wear characteristics of pitch bearings on ground-based test rigs. NREL has also recently begun a research program related to pitch bearing reliability, recognizing its growing importance for wind turbines. The purpose of this paper is to describe a set of instrumentation that was recently installed on a 1.5 MW wind turbine at the NREL Flatirons Campus and provide an example data set. To the authors' knowledge, this will be the first publicly available pitch bearing data collection campaign on an operational wind turbine.

17 WIND ENERGY↗

DOE OSTI2023

RX-ADS: Interpretable Anomaly Detection Using Adversarial ML for Electric Vehicle CAN Data

Recent year has brought considerable advancements in Electric Vehicles (EVs) and associated infrastructures/ communications. Intrusion Detection Systems (IDS) are widely deployed for anomaly detection in such critical infrastructures. This paper presents an Interpretable Anomaly Detection System (RX-ADS) for intrusion detection in CAN protocol communication in EVs. Contributions include: 1) window based feature extraction method; 2) deep Autoencoder based anomaly detection method; and 3) adversarial machine learning based explanation generation methodology. The presented approach was tested on two benchmark CAN datasets: OTIDS and Car Hacking. The anomaly detection performance of RX-ADS was compared against the state-of-the-art approaches on these datasets: HIDS and GIDS. The RX-ADS approach presented performance comparable to the HIDS approach (OTIDS dataset) and has outperformed HIDS and GIDS approaches (Car Hacking dataset). Further, the proposed approach was able to generate explanations for detected abnormal behaviors arising from various intrusions. Furthermore, these explanations were later validated by information used by domain experts to detect anomalies. Other advantages of RX-ADS include: 1) the method can be trained on unlabeled data; 2) explanations help experts in understanding anomalies and root course analysis, and also help with AI model debugging and diagnostics, ultimately improving user trust in AI systems.

42 ENGINEERING↗

DOE OSTI2024

Pore Structures in Detritusphere of Soils Under Switchgrass and Restored Prairie Vegetation Community

Root detritusphere, that is, the soil in the vicinity of decomposing root residues, plays an important role in soil microbial activity and C sequestration. Pore structure (size distributions and connectivity of soil pores) in the detritusphere serves as a major driver for these processes and, in turn, is influenced by the physical characteristics of both soil and roots. This study compared pore structure characteristics in the root detritusphere of soils of contrasting texture and mineralogy subjected to > 6 years of contrasting vegetation: monoculture switchgrass and polyculture prairie systems. Soil samples were collected from five experimental sites in the US Midwest representing three soil types. Soil texture and mineralogy were measured using a hydrometer and x-ray powder diffraction, respectively. The intact cores were scanned with x-ray computed micro-tomography to identify visible soil pores, biopores, and particulate organic matter (POM). We specifically focused on pore structure within the detritusphere around the POM of root origin. Results showed that the detritusphere of coarser textured soils, characterized by high sand and quartz contents, had lower porosity in the vicinity of POM compared with finer textured soils. POM vicinities in finer textured soils had high proportions of large (> 300 μm diameter) pores, and their pores were better connected than in the coarser soils. Lower porosity in the outer (> 1 mm) parts of the detritusphere of switchgrass than of prairie suggested soil compaction by roots, with the effect especially pronounced in the coarser soils. Here, the results demonstrated that soil texture and mineralogy played a major, while vegetation played a more modest, role in defining the pore structure in the root detritusphere.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Root of the matter-Impacts of harvest frequency on soil C and nutrients in switchgrass

We evaluated how harvest frequency affected plant C allocation and soil-water nutrient concentrations in a switchgrass (Panicum virgatumL.) system on the Eastern Shore of Maryland, U.S.A. Switchgrass established in 2023 was harvested once (1Cut), twice (2Cut), or three times (3Cut) during the 2024 growing season to represent potential feedstock-management regimes for anaerobic digestion. Aboveground biomass was measured at each harvest, and root biomass distribution, root C stocks, and soil properties were assessed to 60 cm after the growing season. During 2025, rainfall-synchronized soil water collected with tension lysimeters was analyzed for dissolved inorganic nitrogen (DIN) and inorganic phosphate (Pi) concentrations.

09 BIOMASS FUELS↗

DOE OSTI2022

Control Oriented Model of Cabin-HVAC System in a Long-Haul Trucks for Energy Management Applications

Super Truck II is a 48V mild hybrid class 8 truck with an all auxiliary loads powered purely by the battery pack. Electric Heating Ventilation and Air Conditioning (HVAC) load is the most prominent battery load during the hotel period, when the truck driver is resting inside the sleeper. For the PACCAR Super Truck II (ST-II) project a 48 V battery system provides the required power during the hotel period. A cabin-HVAC model estimates the electric load on the 48V battery system, allowing the control system to implement an efficient energy management strategy that avoids engine idling during the hotel period. The thermal model accounts for the sun load due to the time of day and the geographic location of the truck during the hotel period. The cabin-HVAC model has two parts. First, a grey box model with two heat exchangers (Condenser and Evaporator) working in unison with refrigerant mass flow rate as an input and HVAC load as an output. Second, a two-node cabin model formulated to estimate the cabin temperature as a function of the Global Horizontal Irradiance (GHI), HVAC load and ambient temperature. The models are calibrated using experimental cabin-HVAC system data as for long-haul class 8 truck (e.g. ST-II). Here, the model simulations show that the overall Root Mean Square Error (RMSE) value of 0.4°C between the experimental and simulated cabin temperature.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗