Analysis Code Research Articles

Early Nuclear Fusion Cross-Section Advances 1934–1952 and Comparison to Today’s ENDF Data

We describe the advancing knowledge of fusion cross sections from 1934 through the development of the first thermonuclear tests fielded by Los Alamos (the singular entity denoted Los Alamos Laboratory/Los Alamos Scientific Laboratory/Los Alamos National Laboratory at different times is designated “Los Alamos” in this paper) in the Pacific in 1951–1952; this technical history has not been previously documented. We compare these nuclear reaction cross sections to the current state of their knowledge as codified in the Evaluated Nuclear Data File (ENDF) databases, focusing on the Big Five reactions: 3H ( d , n ) 4 He, 3He ( d , p ) 4 He, 2H ( d , n ) 3 He, 2H ( d , p ) 3 H, and 3H ( t , 2 n ) 4 He. At Oppenheimer’s July 1942 University of California, Berkeley, “galaxy of luminaries” conference, Konopinski suggested that the cross section for 3H ( d , n ) 4 He “DT” could be large, and although Teller described this as an “inspired guess,” we provide evidence instead suggesting that Konopinski knew of a 1938 measurement by Ruhlig that secondary DT reactions were “exceedingly probable.” Bethe’s direction that the DT cross section should be measured at Purdue University (Purdue) in 1943 led to the remarkable and unexpected finding that the DT cross section exceeds deuteron-deuteron (DD) by a factor of 100. This was a game-changing result, making Teller’s dream, i.e., the terrestrial production of fusion energy, feasible. Eyewitness accounts are transcribed from the earliest discoveries of the large magnitude of the resonant DT cross section. A description is given of the Manhattan Project’s early 1942–1944 DD measurements at the University of Chicago, the 1943 DT measurements at Purdue, and the subsequent 1945–1946 DD and DT measurements at Los Alamos. The Los Alamos experiments, led by Bretscher, were the first to extend to very low incident ion center-of-mass energies in the 6- to 50-keV range needed in applications and the first to identify, characterize, and document the 3/2+ “Bretscher state” responsible for the resonance-enhanced DT cross section. The early measurements were based on thick-target experiments that required a knowledge of hydrogen-isotope stopping powers, much of which was informed by 1930s German studies. We end with the high-accuracy APSST (named for Arnold, Phillips, Sawyer, Stovall, and Tuck) measurements at Los Alamos, 1951–1952. The very first 1942–1946 measurements were accurate to about 50% or somewhat better, but by the early 1950s, the cross sections were determined much more accurately, to within a few percent of our best values today, which come from R-matrix Energy Dependent Analysis (EDA) code analyses of the data, most notably the very accurate 1980s–1990 Los Alamos DT and DD fusion data from Jarmie and Brown. We show that Fermi, in his 1945 Los Alamos lectures, anticipated the S-factor (for the DT cross section), which is a concept widely used later in nuclear astrophysics. To this long abstract, we add a final tidbit: Marshall Holloway, a coauthor on the first-ever 1943 DT cross-section measurement at Purdue, went on to lead the engineering and fabrication of the first H-bomb test, Ivy Mike.

Feature Extraction Based on Sparse Coding Approach for Hand Grasp Type Classification

The kinematics of the human hand exhibit complex and diverse characteristics unique to each individual. Various techniques such as vision-based, ultrasonic-based, and data-glove-based approaches have been employed to analyze human hand movements. However, a critical challenge remains in efficiently analyzing and classifying hand grasp types based on time-series kinematic data. In this paper, we propose a novel sparse coding feature extraction technique based on dictionary learning to address this challenge. Our method enhances model accuracy, reduces training time, and minimizes overfitting risk. We benchmarked our approach against principal component analysis (PCA) and sparse coding based on a Gaussian random dictionary. Our results demonstrate a significant improvement in classification accuracy: achieving 81.78% with our method compared to 31.43% for PCA and 77.27% for the Gaussian random dictionary. Furthermore, our technique outperforms in terms of macro-average F1-score and average area under the curve (AUC) while also significantly reducing the number of features required.

BAYESIAN NESTED LATENT CLASS MODELS FOR CAUSE-OF-DEATH ASSIGNMENT USING VERBAL AUTOPSIES ACROSS MULTIPLE DOMAINS.

Understanding cause-specific mortality rates is crucial for monitoring population health and designing public health interventions. Worldwide, two-thirds of deaths do not have a cause assigned. Verbal autopsy (VA) is a well-established tool to collect information describing deaths outside of hospitals by conducting surveys to caregivers of a deceased person. It is routinely implemented in many low- and middle-income countries. Statistical algorithms to assign cause of death using VAs are typically vulnerable to the distribution shift between the data used to train the model and the target population. This presents a major challenge for analyzing VAs, as labeled data are usually unavailable in the target population. This article proposes a latent class model framework for VA data (LCVA) that jointly models VAs collected over multiple heterogeneous domains, assigns causes of death for out-of-domain observations and estimates cause-specific mortality fractions for a new domain. We introduce a parsimonious representation of the joint distribution of the collected symptoms using nested latent class models and develop a computationally efficient algorithm for posterior inference. We demonstrate that LCVA outperforms existing methods in predictive performance and scalability. Supplementary Material and reproducible analysis codes are available online. The R package LCVA implementing the method is available on GitHub (https://github.com/richardli/LCVA).

Prediction of Ground and Building Vibrations Induced by High-speed Trains using a 3D Coupled Numerical Model Based on a Spectral Element Analysis Code

Prediction of Ground and Building Vibrations Induced by High-speed Trains using a 3D Coupled Numerical Model Based on a Spectral Element Analysis Code

Application of BPNN algorithm in thermal-hydraulic analysis of unwrapped LFR core

Due to the complex structure of the LFR fuel rod bundle, refined CFD simulation consumes significant computing resources and time, making it difficult to meet the immediate needs of engineering design and research. This paper introduces a method that integrates the sub-channel level thermal-hydraulic analysis code CorTAF-LBE with the BPNN algorithm to analyze the thermal-hydraulic phenomena within the LFR core. The method has been validated by refined simulation results of the THEADES test section, which indicate that the error is within an acceptable range. The feasibility of its application in LFR fuel assemblies was also evaluated. The flow characteristics and temperature distribution in unwrapped LFR rod bundles are investigated. Due to differences in fuel distribution and flow area, the temperature in the central channel is much higher than that in the side and trapezoidal channels. Three accident conditions, including inlet blockage, center blockage, and outlet blockage, were simulated. The corresponding peak temperatures of the fuel cladding were 670 K, 767 K, and 860 K, respectively, representing an increase of approximately 170 K compared to the nominal conditions. The analysis results effectively demonstrate the 3D temperature distribution of the fluid in the rod bundles, which is significant for reactor design and safety analysis of LFRs.

Vertical load distribution in precast hollow core floors: State of the art and future perspectives

AbstractPrecast prestressed hollow core (HC) floors are widely used in various applications within the construction sector. Such floors are usually designed as single, simply supported elements, although it is known that individual elements forming the floor interact with each other. This article presents the state of the art regarding load redistribution in HC floors in the light of experimental data, current analytical models and code provisions. While this phenomenon is widely known and recognized, only sparse, and often poorly documented experimental data are available, which represent the basis for the assessment and calibration of analytical models. Moreover, even though the available models and code provisions share similar assumptions, their outcomes are in some cases conflicting. Having recognized the existing knowledge gap, the authors outline future perspectives for the development of consistent analytical and numerical approaches supplemented by new experimental data.

Probabilistic fracture mechanics analyses of a reactor pressure vessel using the irradiation embrittlement evaluation based on the Bayesian nonparametric method

In the structural integrity assessment of an embrittled reactor pressure vessel (RPV) based on probabilistic fracture mechanics (PFM), it is crucial to consider both of the mean value and the uncertainty of the embrittlement prediction. Typically, the embrittlement prediction uncertainty is given by a normal distribution, and its standard deviation is determined from the residuals of the measured and predicted values of all data used to develop the embrittlement prediction method. Therefore, the same uncertainty is assumed regardless of neutron fluence and the available data. To overcome this issue, the Japan Atomic Energy Agency recently developed the embrittlement prediction method based on machine learning and Bayesian statistics, i.e., the Bayesian nonparametric (BNP) method, and introduced it to the PFM analysis code. The BNP method can predict the probability distribution according to data scarcity and provide more reasonable uncertainty because it estimates significant uncertainties where the scatter of actual measured data is large and the number of data is small. In this study, PFM analysis for a Japanese model RPV in a pressurized water reactor is conducted using the PFM analysis of structural components in aging light water reactors, where the embrittlement probability distribution calculated using the BNP method is used. Furthermore, the effects of different embrittlement prediction methods and uncertainties on the failure frequency of RPVs are investigated in the PFM analyses, and the results are presented.

A Study on the Level of Customer Satisfaction Towards the Services of Maruti Suzuki

The study investigates customer satisfaction levels regarding Maruti Suzuki services. It employs a mixed-methods approach, combining surveys and interviews to gather comprehensive insights. The research sample includes Maruti Suzuki customers across diverse demographics, ensuring a representative perspective. The study aims to identify key factors influencing customer satisfaction, such as service quality, accessibility, and after-sales support. Statistical analysis and thematic coding of qualitative data enable a nuanced understanding of customer perceptions and preferences. The findings contribute to the existing body of knowledge on automotive service satisfaction and offer practical implications for Maruti Suzuki's service improvement strategies. Ultimately, the research aims to enhance customer experiences and foster long-term loyalty towards the brand. The study aims to explain key determinants of customer satisfaction within the context of Maruti Suzuki's services, including but not limited to service quality, accessibility, communication, and after-sales support. By identifying areas of strength and areas for improvement, the findings of this research will contribute to enhancing the overall customer experience and fostering long-term loyalty towards the Maruti Suzuki brand.

Development of the thermal hydraulic analysis code, TASS/SMR-S, under multi-dimensional motion for a reactor under inclination and rolling conditions

The development of a thermal hydraulic analysis code that considers ship motion is important because it would adjust for additional motion effects that are not present in a land-based system analysis code. The TASS/SMR-S code, a one-dimensional system analysis code, was modified to predict the thermal hydraulic behavior of a nuclear reactor under the conditions of an ocean environment. To validate the improved TASS/SMR-S code, the calculation results were compared with the analytical solutions for a conceptual problem involving swaying, rolling, and compounded motions; experimental data were collected under inclination and rolling conditions. The modified TASS/SMR-S code exhibited good agreement with analytical solutions for the conceptual problem and experimental results obtained under ship motion conditions. In conclusion, the modified code was able to simulate thermal hydraulic behavior under ship motion conditions.

Using Power Analysis to Choose the Unit of Randomization, Outcome, and Approach for Subgroup Analysis for a Multilevel Randomized Controlled Clinical Trial to Reduce Disparities in Cardiovascular Health

We give examples of three features in the design of randomized controlled clinical trials which can increase power and thus decrease sample size and costs. We consider an example multilevel trial with several levels of clustering. For a fixed number of independent sampling units, we show that power can vary widely with the choice of the level of randomization. We demonstrate that power and interpretability can improve by testing a multivariate outcome rather than an unweighted composite outcome. Finally, we show that using a pooled analytic approach, which analyzes data for all subgroups in a single model, improves power for testing the intervention effect compared to a stratified analysis, which analyzes data for each subgroup in a separate model. The power results are computed for a proposed prevention research study. The trial plans to randomize adults to either telehealth (intervention) or in-person treatment (control) to reduce cardiovascular risk factors. The trial outcomes will be measures of the Essential Eight, a set of scores for cardiovascular health developed by the American Heart Association which can be combined into a single composite score. The proposed trial is a multilevel study, with outcomes measured on participants, participants treated by the same provider, providers nested within clinics, and clinics nested within hospitals. Investigators suspect that the intervention effect will be greater in rural participants, who live farther from clinics than urban participants. The results use published, exact analytic methods for power calculations with continuous outcomes. We provide example code for power analyses using validated software.

Validation of OpenMC Code for Low-cycle and Low-particle Simulations in the Neutronic Calculation

Validation of Low-Cycle and Low-Particle OpenMC Simulation Codes for Neutronics Calculations has been conducted. This study validates OpenMC, an evolving open-source neutron analysis code. Validation of Low-Cycle and Low-Particle Codes is crucial as it allows for effective calculations with minimal computational resources. Determining the convergence point of cycles and minimum particles in low-cycle and low-particle calculations enables maintaining calculation accuracy, thus providing sufficiently accurate results. This study demonstrates that a minimum of 15,000 particles, 100 cycles (30 inactive, 70 active), is required for low-cycle simulations. A comparison of k-eff calculation results with the SRAC code for MSR FUJI-12 at 7 burnup points (0-27 MWd/ton) yields a maximum error of 0.7%. These results validate the effectiveness of OpenMC in achieving accurate neutronic calculations with limited computational resources

Experimental investigation of quench front propagation during reflooding in 5 × 5 rod bundle channel with axial uniform power distribution

This experimental study delves into the impact of inlet injection velocity, inlet subcooling, and linear power density on the quench front propagation during reflooding in 5x5 rod bundle channel with axial uniform power distribution. The investigation utilized a film boiling test facility constructed by NUclear Safety and Operation Laboratory (NUSOL) of Xi'an Jiaotong University. The findings demonstrate a discernible sensitivity of the quench front to variations in these parameters, wherein higher linear power density, reduced flow rate, and decreased coolant subcooling lead to delayed reflooding. Moreover, the study derived the surface parameters of the heater rod use self-developed Reflooding Experimental Data Analysis code (REDA). The comprehensive experimental data and empirical models generated in this study hold significant potential for enhancing the safety analysis of nuclear reactors.

CorTAF-LBE: A full scale subchannel-level thermal-hydraulic characteristics analysis code for LBR core based on OpenFOAM

The lead-bismuth cooled fast reactor core adopts box-type design, and the fuel rod bundle is fixed by wrapping wires. The complex geometric structure of the fuel assemblies significantly affects the flow and heat transfer status of the liquid metal coolant. Building upon the open-source CFD platform, OpenFOAM, this work established conservation equations for liquid metal coolant, fuel rod thermal characteristic models, inter-wrapper coolant analysis models, and coupled heat transfer models, and developed the subchannel level thermal-hydraulic analysis code CorTAF-LBE for whole-core analysis of LBR core using the finite volume method. The wire-wrapped rod bundles internal flow and heat transfer experiments of lead-bismuth, carried out based on the THEADES and KYLIN-II circulation loops, were selected to perform verification and validation. The results match well with the experimental data and CFD fine-modeling prediction. The steady-state numerical simulation of three wire-wrapped rod bundle assemblies with inter-wrapper flow was carried out under normal operation condition. The temperature and pressure distributions of the coolant in each subchannel and inter-wrapper flow region, the temperature of cladding and other key thermal-hydraulic parameters were obtained. The role of the inter-wrapper coolant in heat removal from the fuel assemblies was revealed. The work in this paper has referential value for the optimization of lead-bismuth cooled fast reactor design and safety assessment during operation.

A New Analytical Simulation Code of Acoustic-Gravity Waves of Seismic Origin and Rapid Co-Seismic Thermospheric Disturbance Energetics

A New Analytical Simulation Code of Acoustic-Gravity Waves of Seismic Origin and Rapid Co-Seismic Thermospheric Disturbance Energetics

Prediction and Analysis of Transient Turbine Tip Clearance Using Long Short-Term Memory Neural Network

Abstract The transient turbine tip clearance (δ) throughout the engine process is crucial to modern high-performance aero engines. However, there is still a lack of efficient and accurate transient prediction models of tip clearances with active thermal control (ATC) system, especially for the tip clearances of the complex turbine structures with various parameters. This study develops a transient prediction model for the tradeoff between computational efficiency and accuracy, which includes an offline dataset generation process and an online δ prediction process. The offline dataset is first generated using an in-house finite element analysis code, which is validated against a transient tip clearance experiment, and data splicing and sensitivity analysis are applied to enrich the sample features and reduce the input parameters' dimensionality. Then, the long short-term memory neural network (LSTM) is employed to learn the transient tip clearances' timing information. The time consumption for the transient prediction model is significantly shorter than that for the tip clearance calculation method by three orders, and the maximum relative error is as low as 3.59%. In addition, the transient characteristics, including the overshoot value (σ) and the response time (ts), are investigated with different jet Reynolds numbers (Rec) and temperatures (Tfc) of ATC cooling flow. The ts decreases with larger Rec and smaller Tfc due to a more significant cooling effect. However, the σ increases with the increase of Rec and Tfc due to the different sensitivity of cooling parameters. This study provides a reference for the transient tip clearance prediction and the adjustments in the cooling strategies.

Performance evaluation and validation of OpenMC code for criticality analysis of an MTR-type research reactor

This paper assesses the performance of OpenMC, an open-source Monte Carlo code for particle transport, through criticality analysis of an MTR-type research reactor. The evaluation involves validation against experimental data from the NUR research reactor's first fresh fuel core and a code-to-code comparison with MCNP5, using a consistent methodology ensuring identical input conditions. Key parameters, including excess reactivity, control rod worths, shutdown margin, critical configurations, kinetics parameters, neutron flux, power distributions, and peaking factors, were examined. Results indicate good agreement between OpenMC simulations, experimental data, and MCNP5 results, with marginal differences well within acceptable ranges. Discrepancies with experimental data are below 5 %, considering measurement accuracy, while code-to-code comparisons reveal relative differences below 1 % in most cases. This study supports OpenMC's reliability for MTR reactor criticality analysis, affirming the validity of the developed NUR reactor model for future applications and highlighting the code's credibility and applicability in the nuclear reactor simulations.

Development of a fully implicit ODE-solver for containment analysis code

The thermal–hydraulic dynamics in containment are governed by a system of stiff ordinary differential equations (ODEs). A fully implicit discretization scheme is adopted to discretize these ODEs in order to mitigate the effects of stiffness. In comparison with explicit or semi-implicit discretization schemes that are subject to Courant limits on time steps, the fully implicit discretization scheme is more suitable for a containment analysis code that focuses on predicting both short-term and long-term thermal–hydraulic parameters after an accident. This study introduces a general-purpose ODE solver for the containment analysis code. The outline of the solver is as follows: The fully implicit discrete equations lead to a large set of nonlinear equations that need to be solved using Newton’s iterative method. The partial derivative components in the Jacobi matrix are calculated by the perturbation method using finite difference approximation, which avoids the complicated derivation of partial derivatives. The scaling modification technique is incorporated into this ODE solver to deal with significant differences in unknown variable magnitudes, and the line search method is introduced to address the difficulty of obtaining an accurate root estimate with Newton’s method when the initial guess is far from the actual root. This proposed ODE solver was applied to two typical stiff ODE problems to test its stiffness-suppressed ability and to demonstrate that this proposed solver can perform calculations with a very large time step. Then, the CASSIA code, a containment analysis code developed by China Nuclear Power Technology Research Institute Co., Ltd (CNPRI), equipped with this ODE solver, was applied to the CSNI (Committee on the Safety of Nuclear Installations) benchmark problem and the Carolinas Virginia Tube Reactor (CVTR) test 3 problem to preliminarily demonstrate that the proposed ODE solver can perform containment thermal–hydraulic analysis correctly. This study could provide references for the development of a home-made containment analysis code.

Design, assembly and testing of an upgraded aeroacoustics wind tunnel facility

The Aeroacoustics Laboratory in the Department of Aerospace Engineering at Penn State currently serves several areas of experimental research. Most notable in the laboratory is the Anechoic Chamber of which the Aeroacoustics Wind Tunnel is an integral part. In recent years the dominant areas of research have included model aircraft exhaust jets and model rotors for helicopter applications involving detailed noise experiments. In the jet noise area, the applications have included aircraft in both flyover and take-off configurations. In the flyover application the air flow surrounding the exhaust jet has a significant effect on the radiated noise and must be simulated to produce experimental results that will be most useful in preliminary design of noise suppression applications. The Aeroacoustics Wind Tunnel at Penn State serves the purpose for this simulation. During aircraft take-off, the aircraft airspeed is in a range exceeding 250 ft per second, or Mach number of over M = 0.22. In the years preceding 2022, the velocity of the free jet flow of the Penn State facility was limited to less than 200 ft/sec. This paper reports on a project to design upgrades to the existing wind tunnel to improve the test section flow velocity to values closer to the 250 ft/sec target. The approach began with a preliminary design of the return flow ducting to convert the open jet, open return wind tunnel to a closed return tunnel. The concept is to make use of the flow energy in the exhaust of the tunnel to boost the input energy to the inlet fan that drives the flow to the test section. An integral part of the preliminary design involved making use of an upgraded flow analysis computer code to predict the gain in test section velocity of the new facility. For the available horsepower of two fans in the facility, the configurations of the existing and upgraded wind tunnel were entered into this analysis code based on a quasi-one-dimensional formulation. The code included empirical data formulated to include the various shapes of the components of the tunnels. The relative flow velocities in each section used simple incompressible continuity to calculate all velocities in the component sections. The average dynamic pressure in each section is calculated from the flow (constant) density and the velocity squared. Each section had a non-dimensional pressure loss parameter calculated from empirical data (from the relevant literature). The basic code (using the Excel algorithms) was based on a predictor-corrector concept in which the calculation was initialized with the estimated velocity and pressure of the flow at the entrance to the test section. The loss in each following section is estimated to determine the loss in the total pressure and the cumulated loss compared to the gains made at the two fans in the circuit. The initial guess is adjusted based on the total pressure value at the end of the circuit. During the related experiments, measurements of the total and dynamic pressure were performed at several joints between sections and compared to the values predicted in the analysis code. Various settings of the horsepower of the drive fans were used and the results were compared to flow measurements for the tunnel configurations (predominantly for the open return and closed return tunnel setups available before and after the upgrade project.) Results of the analysis and experiments are presented and analyzed together with the remaining activities planned for the coming months.

Protocol for process evaluation of ARTEMIS cluster randomised controlled trial: an intervention for management of depression and suicide among adolescents living in slums in India

IntroductionThere are around 250 million adolescents (10–19 years) in India. The prevalence of mental health-related morbidity among adolescents in India is approximately 7.3%. Vulnerable subpopulations among adolescents such as those...

Adjusting Clinical Plans Based on Social Context.

Social risk data collection is expanding in community health centers (CHCs). We explored clinicians' practices of adjusting medical care based on their awareness of patients' social risk factors-that is, changes they make to care plans to mitigate the potential impacts of social risk factors on their patients' care and health outcomes-in a set of Texas CHCs. Convergent mixed methods. Surveys/interviews explored clinician perspectives on adjusting medical care based on patient social risk factors. Survey data were analyzed with descriptive statistics; interviews were analyzed using thematic analysis and inductive coding. Across 4 CHCs, we conducted 15 clinician interviews and collected 97 surveys. Interviews and surveys overall indicated support for adjustment activities. Two main themes emerged: 1) clinicians reported making frequent adjustments to patient care plans based on their awareness of patients' social contexts, while simultaneously expressing concerns about adjustment; and 2) awareness of patients' social risk factors, and clinician time, training, and experience all influenced clinician adjustments. Clinicians at participating CHCs described routinely adjusting patient care plans based on their patients' social contexts. These adjustments were being made without specific guidelines or training. Standardization of adjustments may facilitate the contextualization of patient care through shared decision making to improve outcomes.