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At least 397 records · Page 22

Advanced defrosting techniques in air source heat pumps: A review of vapor injection, thermal energy storage, and experimental frost accumulation data

Electrification is a critical step for reducing greenhouse gas emissions from heating. Air source heat pumps (ASHPs) are a promising alternative to fossil fuel-based systems due to their high coefficients of performance (COP), dual heating and cooling capability, and lower carbon footprint. However, for ASHPs to achieve widespread adoption, they must operate reliably across all climates, including cold regions. Additionally, defrosting techniques should be energy efficient and minimally disruptive to indoor comfort. Vapor injection (VI) technology can address the high-pressure and high-temperature lift challenges encountered in low ambient conditions. More recently, in addition to enhancing heating performance, VI has also been shown to improve the speed and efficiency of reverse cycle defrosting. Likewise, thermal energy storage (TES) has steadily gained attention for its ability to serve as an auxiliary heat source during both normal operation and defrosting. This review analyzes the benefits and limitations of VI- and TES-assisted defrosting approaches. While both technologies show strong potential individually, no studies to date have explored their combined use in ASHP systems. Additionally, to support continued development of defrosting strategies, both in modeling and experimental work, it is critical to establish frost accumulation data under a range of operating conditions. By compiling the available data from the literature, this paper also highlights the limited availability of such experimental data and the wide variation in frosting and defrosting durations and termination criteria, which are often influenced by system design and test setups.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Land-use analysis using infrastructure representations and high-resolution flood inundation mapping techniques

In the face of climate change and population growth in coastal regions, land-use analysis efforts are more challenging than ever. Land-use decision-makers in coastal communities are burdened with the difficult choices of where to place new homes versus other assets. While there has been an increased focus on hazard mitigation and disaster resilience in the field of planning, evidence points towards continued development in risk-prone areas including flood zones. Residential development within flood zones specifically continues to be a major issue. To help counter this trend, this study introduces a novel land-use analysis method, coupling topographic flood inundation mapping techniques with digital elevation model (DEM) adaptations. This Topographic Model Scenario Generation workflow can be used by planners early in the land-use decision making process and provides an alternative to high-computational hydraulic models. The analysis also includes the identification of strengths and weaknesses of topographic models' recognition of built infrastructure assets, adding to a limited body of knowledge addressing recommended uses of such models. Levees and canals prove particularly functional in this context while detention ponds less so, likely due to a lack of total water mass accountability. Lastly, we provide a functional demonstration in Southeast Texas to illustrate the workflow's ability to create multiple infrastructure scenarios and visualize their effects across different flood events.

42 ENGINEERING↗

Ball Motion and Near-Field Spray Characteristics of a Gasoline Direct Injection Injector using an X-ray Phase-Contrast Imaging Technique under High-Injection Pressures

Here, the purpose of this study is to visualize the ball (needle) motion and near-field spray characteristics of a gasoline direct injection injector under different injection conditions and analyze the effect of the internal structure of the injector on the ball motion, near-field spray velocity, and post-injection process. The injection pressure is set to 10MPa, 20 MPa, and 30 MPa, and the energization duration is fixed at 1.5 ms. An advanced X-ray technique with high transmittance and low scattering, is used to visualize the internal structure and near-field spray characteristics of the injector, which is impossible with general light sources. The ball is found to tilt to the right in the Y-axial direction during stable motion because the driving force of fuel on the ball is larger on the left side owing to the larger distance of the ball from the left wall. In addition, during stable motion, the near-field velocity of a hole with a smaller inlet angle is significantly higher than that of a hole with a larger inlet angle. The hole with a smaller inlet angle display better atomization characteristics during the post-injection process under all values of injection pressure.

47 OTHER INSTRUMENTATION↗

Introducing a novel technique for measuring hydrogen crossover in membrane-based electrochemical cells

Hydrogen crossover that is the unwanted hydrogen permeation across the membrane driven by the difference of gas concentrations causes a critical concern of safety and efficiency for electrochemical cells, such as fuel cells and electrolyzer cells. Although the hydrogen crossover measurement in fuel cells that employ platinum based catalysts is simple and widely used in laboratory settings, it is questionable to apply existing limiting current method to water electrolyzer cells and alkaline exchange membrane (AEM) systems, which is due to the typical catalyst materials used and membrane properties, respectively. In this work, we demonstrate the operation of a compact and low-cost method of measuring hydrogen crossover that works for both AEM and proton exchange membrane (PEM) systems. The method entails a tandem configuration that utilizes an upstream crossover cell with a downstream cell in hydrogen pump configuration to measure the crossover in the cell of interest. We have successfully measured the hydrogen crossover with different membranes at various differential pressures. The developed method can be applied to catalyst-free membranes (both PEM and AEM) as well as PGM free catalyst containing cells. It will be a promising technique for measuring hydrogen crossover in-situ for a real operating membraned-based electrochemical cell or stack.

08 HYDROGEN↗

Hourglass control in staggered-grid hydrodynamics using virtual element stabilization techniques

Numerical simulations using the staggered-grid hydrodynamics (SGH) discretization suffer from hourglass instabilities. In this work, we develop a stabilization method to suppress the hourglass instabilities using techniques from the virtual element method (VEM). The stiffness matrix of the VEM consists of two terms: the consistency matrix which is rank deficient and the stability matrix. Here, we first show that in two dimensions and on general polygons, the stiffness matrix of the SGH is identical to the consistency matrix of the linear VEM for both the diffusion equation and the linear elasticity equation. These analyses explain the origin of the hourglass instabilities of the SGH discretization method, and establish a theoretical foundation for our proposed stabilization method by augmenting the stiffness matrix of the SGH discretization using the VEM stability matrix. Then, we present numerical examples using Lagrangian SGH simulations. The numerical experiments demonstrate that the proposed VEM stabilization method is effective at eliminating hourglass modes in the SGH discretization.

97 MATHEMATICS AND COMPUTING↗

Dopant segregation in YAG single crystal fibers grown by the laser heated pedestal growth technique

In this work, we report self-segregation of dopants in a crystal matrix within a single crystal (SC) fiber. Neodymium and holmium-doped yttrium aluminum garnet (YAG) fibers were grown using the Laser Heated Pedestal Growth (LHPG) technique and cross-sectional dopant concentration was measured using electron-probe micro-analysis. It was observed that the degree of auto-segregation of the rare-earth dopant depended on the difference in ionic size of the dopant ion and the Y 3+ ion in the YAG matrix. While holmium showed little tendency to self-segregate, the concentration of neodymium ions varied as much as 25% across the cross-section of the fiber. Strong correlation between the dopant concentration profile and fiber draw speed was also demonstrated. Since the local refractive index depends on the concentration of dopants, a refractive index profile can be achieved by a dopant profile across the fiber cross-section. Engineered index profiles can be realized by varying growth conditions, dopants, crystal matrix, etc. Such an approach is promising in applications such as the development of monolithic SC fibers with graded-index profiles.

36 MATERIALS SCIENCE↗

Characterizing soil water content variability across spatial scales from optimized high-resolution distributed temperature sensing technique

Fiber-optic Distributed Temperature Sensing, when combined with the Single-probe Heat-pulse technique can measure soil moisture (θ) across spatial scales. The key limitation of this system is in obtaining the relationship between soil thermal conductivity (λ) and θ for a specific field. Using the Department of Energy Atmospheric Radiation Measurement (ARM) site, this study tested a new methodology to account for the spatial variability in the λ-θ relationship using a Gaussian processes model. The resulting accurate θ measurements (RMSE = 0.03 m 3 m –3 ) were used to characterize the spatial variability of θ across scales and to develop an empirical equation that can correct for the changes in the θ spatial variability observed at different spatial resolutions. In addition, the number of required samples to accurately characterize θ and its variability over scales ranging from 5 m and 350 m were estimated. Finally, these findings provide key information to scale soil moisture from centimeters to hundreds of meters for process understanding.

54 ENVIRONMENTAL SCIENCES↗

Friction-based riveting technique for AZ31 magnesium alloy

Rivet materials used in the aerospace and automotive industries are typically alloys of aluminum (Al) or steel. Magnesium (Mg) is an attractive alternative because it is 33% and 75% lighter than Al and steel, respectively. However, a primary barrier for using Mg as rivet material is its poor formability at room temperature, resulting in brittle fracture of the rivet head during cold riveting. Hot riveting is possible but suffers from high cycle time due to the need for pre-heating. A new friction-based riveting technique, Rotating Hammer Riveting (RHR), is reported to fully form AZ31 Mg rivet heads in a mere 0.23 seconds cycle time. Heat and pressure generated through severe plastic deformation during the process was sufficient to form the Mg rivet head without the need for a separate pre-heating operation. Due to dynamic recrystallization, AZ31 Mg grains in the rivet head were significantly refined from about 15 to 2.6 µm during RHR, which favors the formability of Mg rivet by triggering grain boundary sliding and reducing plastic anisotropy of Mg. In addition, RHR joints showed a metallurgical bond between the rivet head and top sheet, which eliminates a significant pathway for corrosion.

36 MATERIALS SCIENCE↗

A snapshot of high-entropy alloy processing techniques and their effects on resulting mechanical properties

High-entropy alloys (HEAs) exhibit exceptional strength, corrosion resistance, and thermal stability, making them promising candidates for nuclear, aerospace, and other extreme applications. While most prior work has focused on compositional design, manufacturing techniques themselves can alter microstructure and mechanical properties as dramatically as alloy chemistry. This review compiles and compares the effects of processing routes—including arc melting, induction melting, mechanical alloying with spark plasma sintering, and additive manufacturing—on the structure and properties of HEAs. Quantitative comparisons highlight, for example, that SPS-processed alloys can achieve ∼20–45 % higher yield and tensile strength than arc-melted counterparts, while Bridgman solidification produces nearly single-crystal structures with elongation to failure exceeding 80 %. Additive manufacturing routes such as selective laser melting offer fine microstructures but also introduce anisotropy and porosity, leading to yield strengths spanning 100–600 MPa for the same composition. By synthesizing such results, this review provides actionable insight into how processing routes interact with HEA core effects (high entropy, lattice distortion, sluggish diffusion, and cocktail effect) to determine performance, thereby offering a practical guide for optimizing manufacturing strategies.

36 MATERIALS SCIENCE↗

Multi-technique characterization of spray coated and roll-to-roll coated gas diffusion fuel cell electrodes

Here this work reports the characterization of catalyst layer (CL) structure and composition for a set of gas-diffusion electrodes (GDEs) fabricated by different coating methods with the goal of developing a better understanding of CL processing-structure-property-performance relationships. The CL coating techniques used in this study were ultrasonic spray coating, and two roll-to-roll (R2R) methods - gravure and slot die. Scanning transmission electron microscopy (STEM) coupled with X-ray energy dispersive spectroscopy (EDS) analysis of GDE cross-sections provided bulk information, while scanning electron microscopy (SEM) with EDS and X-ray photoelectron spectroscopy (XPS) were used to investigate the near surface and surface composition of the CLs that will be in direct contact with the membrane once the membrane electrode assembly (MEA) is constructed. This study demonstrates that common quantification parameters, namely the F:Pt ratio extracted from cross-sectional STEM-EDS maps and top-down CL measurements with SEM and XPS, along with roughness parameters quantified from SEM micrographs are useful parameters in explaining and potentially predicting performance trends. Additionally, it highlights the importance of understanding key CL surface properties for advancing the manufacturability of high-performance components for polymer electrolyte membrane (PEM) technologies.

30 DIRECT ENERGY CONVERSION↗

Measurement of grain boundary strength of Inconel X-750 superalloy using in-situ micro-tensile testing techniques in FIB/SEM system

Grain boundaries (GBs), known as two-dimensional defects, are omnipresent in polycrystalline metallic alloys and thus influence a wide range of mechanical properties under different environmental conditions like irradiation and corrosion. Therefore, quantifying the strength of individual GBs is critical for understanding the degradation of mechanical properties of materials under different conditions. In this study we developed an efficient approach for the fabrication of micro-tensile specimens with a GB almost perpendicular to the tensile direction, which is expected to advance the development of individual GB tensile testing at micro or nanoscale in a wide scope of materials. Further, an in-situ cantilever micro-tensile testing method was developed and used to quantify the strength of a Σ3 GB in Inconel X-750 with the combination of finite element modeling. The average ultimate tensile strength (UTS) of a non-irradiated Σ3 GB is estimated at around 1.4 GPa, comparable to that of a neutron-irradiated Σ3 GB with a dose of ~1.5 dpa (1.3 GPa). Moreover, the in-situ push-to-pull micro-tensile testing technique developed in this work provides valuable insights into the high-angle GB deformation and fracture behavior. This method generates qualitatively similar ductility behavior before and after neutron irradiation as the bulk material testing. However, the ductility and UTS values obtained from this method are different from bulk measurements due to vastly different specimen dimensions.

36 MATERIALS SCIENCE↗

A short account of thermoelectric film characterization techniques

Thermoelectric films and periodic structures have particularly intriguing electrical and thermal transport features due to their low dimensionality. As a result, they have piqued the attention of researchers from across the spectrum of disciplines. Their applications span from cooling fast CPUs to providing energy for wearable devices. The progress in the techniques for synthesizing TE materials and fabricating thin films has facilitated the emergence of a flourishing research domain in the field of electrical and thermal transport at the nanoscale. Further, a significant proportion of contemporary electronic, opto-electronic, and solar energy components are composed of materials featuring numerous interfaces and nanoscale contacts. Consequently, it is imperative to explore the thermal energy transfer and charge carrier transport across the films with thickness dimensions in the nanometer range. The development of cutting-edge approaches for grasping complicated processes at the nanoscale is critical. This review provides a concise overview of the prevalent methodologies developed over the last two decades and employed for the characterization of the Seebeck coefficient and electrical and thermal conductivity of thermoelectric films.

36 MATERIALS SCIENCE↗

Evaluation of material accountancy techniques for 233 Pa from thorium nuclear fuels

Thorium is a promising alternative to uranium as nuclear fuel with advantages such as higher abundance, lower production of long-lived transuranic elements, and potentially better proliferation resistance. However, thorium presents a potential pathway for proliferation where produced 233 Pa can be diverted for the clandestine production of safeguarded 233 U. To prevent this, the ability to detect and measure 233 Pa must be assessed. This paper reviews several nuclear material accountancy techniques to determine their suitability for detecting 233 Pa extracted from irradiated thorium fuel. Hybrid K-edge densitometry and passive gamma spectroscopy have been found to be the best options based on technology maturity, cost, accuracy, and acquisition time. Thorium can be used in various reactor designs such as pressurized water reactors (PWRs), Canada deuterium uranium (CANDU) reactors, and molten salt reactors (MSRs). Therefore, thorium-uranium oxide fueling was modeled for three representative reactors (PWR, CANDU, MSR), burning the fuel to 47 GWd/MTHM for PWR, 19 GWd/MTHM for CANDU, and at a steady power of 52.711 MW/MTHM for MSR. Within each model, the protactinium element in the used fuel was extracted and its isotopic content analyzed. Simulated results indicated that 233 Pa can be detected using passive gamma spectroscopy in each fuel type at all decay times (0–300 days) following separation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Computational techniques for the analysis of small signals in high-statistics neutrino oscillation experiments

The current and upcoming generation of Very Large Volume Neutrino Telescopes – collecting unprecedented quantities of neutrino events – can be used to explore subtle effects in oscillation physics, such as (but not restricted to) the neutrino mass ordering. The sensitivity of an experiment to these effects can be estimated from Monte Carlo simulations. With the high number of events that will be collected, there is a trade-off between the computational expense of running such simulations and the inherent statistical uncertainty in the determined values. In such a scenario, it becomes impractical to produce and use adequately-sized sets of simulated events with traditional methods, such as Monte Carlo weighting. In this work we present a staged approach to the generation of expected distributions of observables in order to overcome these challenges. By combining multiple integration and smoothing techniques which address limited statistics from simulation it arrives at reliable analysis results using modest computational resources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Extracting low energy signals from raw LArTPC waveforms using deep learning techniques — A proof of concept

Here, we investigate the feasibility of using deep learning techniques, in the form of a one-dimensional convolutional neural network (1D-CNN), for the extraction of signals from the raw waveforms produced by the individual channels of liquid argon time projection chamber (LArTPC) detectors. A minimal generic LArTPC detector model is developed to generate realistic noise and signal waveforms used to train and test the 1D-CNN, and evaluate its performance on low-level signals. We demonstrate that our approach overcomes the inherent shortcomings of traditional cut-based methods by extending sensitivity to signals with ADC values below their imposed thresholds. This approach exhibits great promise in enhancing the capabilities of future generation neutrino experiments like DUNE to carry out their low-energy neutrino physics programs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Novel imaging technique for thermal neutrons using a fast optical camera

A novel imaging technique for thermal neutrons using a fast optical camera is presented. Thermal neutrons are reacted with 6 Lithium to produce a pair of 2.73 MeV tritium and 2.05 MeV alpha particles, which in turn interact in a thin layer of LYSO crystal scintillator to produce a localized flash of light. These photons are directed by a pair of lenses to a micro-channel plate intensifier, and its output is connected to the optical camera, TPX3CAM. The results from the camera are reconstructed through a custom algorithm. Various cutting parameters were found through data analysis to eliminate the background, and they were shown effective in matching the simulated rate of the neutron source. The system is fast with 40 ns decay time and allows free-space light collection, both vastly enhances flexibility of neutron detection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Machine Learning technique for isotopic determination of radioisotopes using HPGe γ-ray spectra

γ-ray spectroscopy is a quantitative, non-destructive technique that may be utilized for the identification and quantitative isotopic estimation of radionuclides. Traditional methods of isotopic determination have various challenges that contribute to statistical and systematic uncertainties in the estimated isotopics. Furthermore, these methods typically require numerous pre-processing steps, and have only been rigorously tested in laboratory settings with limited shielding. Here, in this work, we examine the application of a number of machine learning based regression algorithms as alternatives to conventional approaches for analyzing γ-ray spectroscopy data in the Emergency Response arena. This approach not only eliminates many steps in the analysis procedure, and therefore offers potential to reduce this source of systematic uncertainty, but is also shown to offer comparable performance to conventional approaches in the Emergency Response Application.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗