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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Development of a Convolutional Neural Network Classifier for Data Starved Spectra - 20199

The Institute for Clean Energy Technology (ICET) at Mississippi State University is exploring the utility of machine learning in augmenting its mobile radiation surveying platforms, which are currently being developed as means to survey depleted uranium contaminated areas in support of remediation and decommissioning efforts. Mobile survey platforms provide a means to efficiently scan large areas of interest while reducing human exposure to radiation and other hazards. The survey platforms can also be used for scanning for any gamma emitting isotope in addition to depleted uranium. The spectral data that the platforms collect may be data starved with relatively low counts and poorly defined spectral features depending on the speed of the platforms and scintillation detector selection. Such data-starved spectra are difficult to use for isotope identification, requiring advanced knowledge of the possible radionuclides that could be present and environmental factors that could attenuate signals or introduce background noise. These factors in combination with the volume of survey data increases the time it takes to perform analysis of survey data when the source type is unknown. There are a number of algorithms in the field of machine learning that can be used to classify data that would be challenging and time-consuming for a human to identify. Supervised machine learning algorithms train models based on extensive amounts of human-labeled training data. Once sufficiently trained, these models can be used to quickly make high-fidelity predictions on new data. Convolutional neural networks are machine learning algorithms that excel in learning representations of 'shapes'. They do this by taking numerical input data and convolving them with spatial feature detectors referred to as filters. These filters are incrementally adjusted to reduce the prediction error on the data during the backpropagation step of training. Discussed in this paper is the development of a convolutional neural network classifier (CNNC) that can utilize spectral survey data for source discrimination and isotope identification. Bench-top laboratory experiments data using LaBr{sub 3}(Ce) scintillation detectors were used to train and evaluate the performance of the developed CNNC. The CNNC is capable of discriminating a variety of gamma emitting source types, differentiating different forms of uranium (depleted vs. natural), and estimating the amount of uranium for a known geometry. The discussed CNNC may be useful in scenarios where survey systems are deployed in situations where hazardous radioactive material maybe present, but the type is unknown. When used in remediation applications the CNNC can be used to screen-out false positives, helping reduce remediation costs. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

A Particle-in-Cell Method for Plasmas with a Generalized Momentum Formulation, Part II: Enforcing the Lorenz Gauge Condition

In a previous paper Christlieb et al. (A particle-in-cell method for plasmas with a generalized momentum formulation, part I: Model formulation, 2024), we developed a new particle-in-cell (PIC) method for the relativistic Vlasov–Maxwell system in which the electromagnetic fields and the equations of motion for the particles were cast in terms of scalar and vector potentials through a Hamiltonian formulation. This new method evolved the potentials under the Lorenz gauge using integral equation methods. New methods to construct spatial derivatives of the potentials that converge at the same rates as the fields were also presented. The new particle method was compared against standard explicit discretizations, including the well-known FDTD-PIC method, for a range of applications involving sheaths and particle beams. Here, this paper extends this new class of methods by focusing on the enforcement the Lorenz gauge condition in both exact and approximate forms using co-located meshes. A time-consistency property of the proposed field solver for the vector potential form of Maxwell’s equations is established, which is shown to preserve the equivalence between the semi-discrete Lorenz gauge condition and the analogous semi-discrete continuity equation. Using this property, we present three methods to enforce a semi-discrete gauge condition. The first method introduces an update for the continuity equation that is consistent with the discretization of the Lorenz gauge condition. Both the finite difference and spectral implementations satisfy this discrete gauge condition to machine precision. The second approach we propose enforces a semi-discrete continuity equation using the boundary integral solution to the field equations. The potential benefit of this approach is that it eliminates spatial derivatives that appear on the particle data, namely the current density, which is often calculated by linear combinations of low-order spline basis functions. This method is ideally suited to boundary integral equation methods that invert multi-dimensional operators without dimensional splitting techniques and will be the subject of future work. The third approach introduces a gauge correcting method that makes direct use of the gauge condition to modify the scalar potential and uses local maps for both the charge and current densities. This results in a gauge error, as the maps do not enforce the continuity equation. The vector potential coming from the current density is taken to be exact, and using the Lorenz gauge, we compute a correction to the scalar potential that makes the two potentials satisfy the gauge condition. This method also enforces the gauge condition to machine precision. We demonstrate two of the proposed methods in the context of periodic domains. Problems defined on bounded domains, including those with complex geometric features remain an ongoing effort. However, this work shows that it is possible to design computationally efficient methods that can effectively enforce the Lorenz gauge condition in a non-staggered PIC formulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Chronostratigraphy of talus flatirons and piedmont alluvium along the Book Cliffs, Utah – Testing models of dryland escarpment evolution

Research on the evolution of dryland escarpments and what drives and controls their erosional retreat have been limited by a lack of chronologically constrained records. Prior investigations of escarpments in the southwestern U.S. and globally garner two endmember conceptual models -- one focused on bottom-up baselevel drivers and autogenic variations in piedmont and toeslope erosion processes, the other focused on the role of climate as a top-down forcing mechanism on sediment production and transport from cliffs. In this work, we test these conceptual models along a section of the Book Cliffs in central Utah, where climate has varied strongly and baselevel has fallen significantly over the late Quaternary. Four generations of talus flatirons and piedmont terraces are preserved in the study area we date them by optically stimulated luminescence and 10Be-exposure techniques. OSL depositional ages cluster into four generations of deposits with mean ages and mean standard errors of 117.8 ± 6.7 ka, 83.4 ± 3.3 ka, 52.4 ± 1.8 ka, and 5.6 ± 0.3 ka. 10Be-exposure results from talus boulders protruding from flatirons confirm that the youngest generation of talus is Holocene, with recent rock-fall boulders still being received on the landform top. Older flatiron generations produce incoherent, minimum exposure ages reflecting an increasing dominance of in situ boulder weathering and a steady-state denudation rate of ~45 mm/ky after tens of thousands of years. Based on the chronostratgraphy and correlation of talus and piedmont deposits, we interpret climate as the primary control on escarpment evolution. Depositional ages do not correspond to glacial epochs as historically presumed, but instead to episodes of intermediate and unstable or variable Pleistocene climate during Marine Isotope Stage-3 and 5 a/b. Results support the significance of high climate variability at millennial timescales in driving both sediment production by mass wasting from the cliff as well as sediment storage and reworking along the piedmont. In contrast, wetter climates of glacial epochs apparently caused greater erosion and sediment transport to trunk drainages. Our chronology also reveals a systematic decrease in deposit age with increasing distance up the piedmont from the regional baselevel of the Price River, consistent with transient fluvial incision and terrace abandonment. The Book Cliffs record notably does not correlate with similarly constrained records in Spain or the contrasting record from the Negev, yet they all share the feature of enhanced talus deposition and cliff retreat corresponding to climate instability rather than in response to steady glacial-climate conditions. Thus, we outline a model of escarpment evolution and retreat governed largely by top-down climate-forcing of sediment production and transport during climate variability, with local changes in baselevel and erosional processes on the piedmont being a modifying, secondary factor.

58 GEOSCIENCES↗
DOE OSTI2026

Developing Source Term Database for Advanced Reactors

A source term database is crucial to informing nuclear emergency response measures, enabling emergency responders to assess the potential severity of nuclear and radiological consequences. In recent times, various advanced reactor designs have come into operation, are under construction, or are being designed and developed. This report documents an effort carried out to develop a source term database for advanced reactors. The report covers key design features of these reactors and discusses radioactivity buildup and source term inventories of dose-significant radionuclides in the reactor core. For neutronic and depletion analyses, we used the SCALE code system, a computational suite for reactor physics, depletion, criticality, and sensitivity/uncertainty quantification. We used SCALE/TRITON to perform depletion calculations to predict cycle length and discharge burnup and to generate the ORIGEN reactor library. Subsequently, we used SCALE/ORIGAMI to calculate radioactivity buildup and, thereby, the source term inventories at the targeted discharge burnup, using the ENDF/B-VII.1 nuclear data library. This report covers several advanced reactors, including the KLT-40S, RITM-200N, VOYGR, and eVinci. However, other reactors, such as the RITM-200S and ARC-100, have yet to be investigated and will be explored in future efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Systematic Enterprise Risk Management by Integrating the RISMC Toolkit and Cost-Benefit Analysis (Final Report)

The goal of this research is to theorize and quantify the relationships between safety and the financial performance of nuclear power plants (NPPs). The Socio-Technical Risk Analysis (SoTeRiA) theoretical framework, which connects the social aspects (e.g., safety culture) and structural features (e.g., safety practices) of an organization with organizational safety and financial risks, is used to theorize the direct and indirect relationships between safety and the financial performance of NPPs. An Integrated Enterprise Risk Management (I-ERM) methodological framework is developed to operationalize SoTeRiA to quantify NPP safety and financial performance in a unified platform where their underlying physical degradation mechanisms, coupled with maintenance performance (considering human and organizational factors), are explicitly incorporated to depict the interconnections and dependencies between safety and financial performance. In this study, NPP safety refers to both occupational safety and system safety (estimated from Probabilistic Risk Assessment, PRA), and financial performance refers to the monetary values associated with NPP operation and maintenance (O&M) strategies. This report covers a case study demonstrating the feasibility of the I-ERM methodological framework. More detailed development of one of the I-ERM modules, i.e., Probabilistic Physics-of-Failure (PPoF) analysis, and its connection with other I-ERM modules is demonstrated in a second case study. The outcome of this research will help NPP decision-makers create cost-saving maintenance strategies while maintaining safety by providing cost- and risk-informed recommendations regarding maintenance work processes and operational strategies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Metalorganic chemical vapor deposition of ZnGeN 2 films on GaN: effects of cation stoichiometry on surface morphology and crystallinity

Novel optoelectronic device designs based on the heterostructures of III-N and II-IV-N 2 are promising to advance device performance significantly. For example, by utilizing InGaN-ZnGeN 2 quantum well (QW) structures instead of pure InGaN, the band structure engineering in the QW active region can lead to improved electron-hole wavefunction overlap, and thus enhance the radiative efficiency for photon generation. These novel heterostructures have great potential to address the current challenge of low quantum efficiency in InGaN QW based light emitting diodes emitting in green and beyond. The materials development of ZnGeN 2 is still at an early stage as compared to the much matured GaN material system. In an ideal octet rule preserving ordered structure of ZnGeN 2 , every N atom is coordinated by exactly two Zn and two Ge atoms. However, local violation of octet rule can be caused by non-ideal coordination of N by the cations. The disordered structure is thermodynamically less favorable but can still be achieved, for example, in kinetics-limited growth regime. The ordered ZnGeN 2 has a bandgap very close to that of GaN (~3.4 eV) and a lattice mismatch of <0.1% with GaN. Interestingly, the valence band of ZnGeN 2 has been predicted to be ~1 eV above that of GaN, which has inspired novel designs for high efficiency light emitters. In this work, we investigated the metalorganic chemical vapor deposition (MOCVD) of ZnGeN 2 films on GaN/c-sapphire templates. Diethylzinc (DEZn), germane (GeH4) and ammonia were used as the precursors for Zn, Ge and N, respectively. A systematic study was conducted to investigate the cation stoichiometry as a function of growth temperature (TG), total reactor pressure (P) and DEZn/GeH 4 molar flow rate ratio (RII/IV). Under the investigated growth window, the Zn/(Zn+Ge) composition in the films, determined from energy dispersive X-ray spectroscopy, decreased monotonically with increase in TG but increased with increase in P and RII/IV. Atom probe tomography data did not indicate the presence of any secondary phases such as Zn 3 N 2 or Ge 3 N 4 . The surface morphology and crystallinity of the grown films had strong correlation with the Zn/(Zn+Ge) composition. The scanning electron microscopy images showed that the near-stoichiometric films have planar surfaces whereas Zn-rich films had crystallites on their surface and the Zn-poor films had faceted surface. Scanning transmission electron microscopy (STEM) imaging revealed that the Zn-rich and Zn-poor films have columnar and filament-like morphology, respectively, whereas the near-stoichiometric films have continuous film-like cross-sectional morphology. TEM nano-diffraction patterns as well as X-ray diffraction 2θ-ω scan profiles indicate that the near stoichiometric films are single crystalline. Nano-diffraction pattern of the stoichiometric films resembled that of a disordered ZnGeN 2 structure. Room temperature Raman spectra of near-stoichiometric films showed only the phonon density of states like features of a cation disordered ZnGeN 2 . Cathodoluminescence and photoluminescence spectra measured at different temperatures had similar features with peak emission wavelength at ~ 2 eV. In conclusion, the stoichiometry of ZnGeN 2 films can be widely tuned by tuning the MOCVD growth parameters. The surface morphology and the crystallinity of the films were found to have strong correlation with the Zn/(Zn+Ge) composition. The stoichiometric ZnGeN 2 films grown on GaN were demonstrated with uniform surface morphology and high crystalline quality. The results from this work will provide pathway to implement ZnGeN 2 in device structures.

Karim, Md Rezaul↗
DOE OSTI2025

A change language for ontologies and knowledge graphs

Ontologies and knowledge graphs (KGs) are general-purpose computable representations of some domain, such as human anatomy, and are frequently a crucial part of modern information systems. Most of these structures change over time, incorporating new knowledge or information that was previously missing. Managing these changes is a challenge, both in terms of communicating changes to users and providing mechanisms to make it easier for multiple stakeholders to contribute. To fill that need, we have created KGCL, the Knowledge Graph Change Language (https://github.com/INCATools/kgcl), a standard data model for describing changes to KGs and ontologies at a high level, and an accompanying human-readable Controlled Natural Language (CNL). This language serves two purposes: a curator can use it to request desired changes, and it can also be used to describe changes that have already happened, corresponding to the concepts of “apply patch” and “diff” commonly used for managing changes in text documents and computer programs. Another key feature of KGCL is that descriptions are at a high enough level to be useful and understood by a variety of stakeholders—e.g. ontology edits can be specified by commands like “add synonym ‘arm’ to ‘forelimb’” or “move ‘Parkinson disease’ under ‘neurodegenerative disease’.” We have also built a suite of tools for managing ontology changes. These include an automated agent that integrates with and monitors GitHub ontology repositories and applies any requested changes and a new component in the BioPortal ontology resource that allows users to make change requests directly from within the BioPortal user interface. Overall, the KGCL data model, its CNL, and associated tooling allow for easier management and processing of changes associated with the development of ontologies and KGs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Generic FEPs Catalogue and Salt Knowledge Archive

This report describes the development of a comprehensive catalogue of generic features, events, and processes (FEPs) that are potentially important for the post-closure performance of a repository for high-level radioactive waste (HLW) and spent nuclear fuel (SNF) in salt (halite) host rock. The FEPs and other supporting information have been entered into a “SaltFEP” Database. The generic salt repository FEPs include consideration of relevant FEPs from a number of U.S., Dutch, German, and international FEP lists and should be a suitable starting point for any repository program in salt host rock. The salt FEP catalogue and database employ a FEP classification matrix approach that is based on the concept that a FEP is typically a process or event acting upon or within a feature. The FEP matrix provides a two-dimensional structure consisting of a Features/Components axis that defines the “rows” and a Processes/Events axis that defines the “columns” of the matrix. The design of the FEP classification matrix is consistent with repository performance assessment – the Features/Components axis is organized vertically to generally correspond to the direction of potential radionuclide migration (from the waste to the biosphere) and the Processes/Events axis is designed to represent the common two-way couplings between thermal processes and other processes (such as thermal-mechanical or thermal-hydrologic processes). Related FEPs can be easily identified – related FEPs will typically be grouped in a single matrix cell or aligned along a common row (Feature/Component) or column (Process/Event). The online SaltFEP database can be downloaded from www.saltfep.org. It contains the FEP matrix, the FEPs, and the associated processes for each FEP. It provides a starting point to create and document site-specific individual FEPs. Furthermore, the FEP matrix is connected to the Salt Knowledge Archive (SKA), a database of about 20,000 references and documents representing the historical knowledge on radioactive disposal in salt. This work is the result of an ongoing collaboration between researchers in the U.S., the Netherlands, and Germany, and supports the NEA Salt Club Mandate. It builds upon prior work which is documented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

DECOVALEX-2023: Task C Final Report

The Full-scale Emplacement (FE) heater experiment at the Mont Terri Underground Rock Laboratory (URL) was designed and conducted by Nagra to replicate an emplacement tunnel of Nagra’s reference repository design at 1:1 scale. Alongside testing the technical feasibility of constructing disposal tunnels, emplacing waste containers in the tunnels and then backfilling them, the main goals of the FE experiment are (1) to obtain a better understanding of the coupled effects of induced thermo-hydro-mechanical (THM) processes that may occur and (2) to validate existing coupled THM models (Müller et al., 2017). A key aspect of ensuring safety for repositories located in low-permeability rock involves minimizing any damage to the rock itself, thereby preserving its integrity and promoting a stable environment Amongst a number of processes that could damage the rock is the increase in pore pressure due to thermal loading caused by heat emitted from the waste. To reduce the potential damage of the rock, it is important to analyse the evolution of heat over time due to the heat load of the containers and assess possible consequences by coupled THM models. The aim of Task C of DECOVALEX-2023 was to build 3D numerical models of the FE experiment, focussing in particular on the heating induced pore pressure change in the Opalinus Clay. Data from a large number of sensors were available from the FE experiment for model comparison. These sensors measured temperature and relative humidity in the bentonite around the heaters, and temperature, pressure and displacement/strain in the surrounding Opalinus clay. Data were available from the start of excavation (April 2012) up to August 2020 for most sensors (more than 5 years from the start of heating in December 2014). To fulfil the overall aim of the task, the work was broken down into a number of steps, starting with simpler models to build confidence in each team’s approach and then moving to more complex models that better represent the FE experiment. Step 0 consisted of 2D benchmark models, gradually increasing the number of processes that are represented from thermal (T) only models in Step 0a, to coupled thermal hydraulic (TH) models in Step 0b with a representation of changing porosity, to coupled thermo-hydro-mechanical (THM) models in Step 0c, where porosity changes are calculated by the mechanical model. A detailed specification of processes, parameters, initial and boundary conditions was provided for this step, with the ambition that all teams would work towards close agreement in their model results, thus building confidence in the model implementations. vi It was not straightforward to achieve agreement between the teams, so additional steps (Step 0b2, 0b3, 0c2, 0c3) were added along with derivation of some analytical solutions against which the models could be compared. The reasons for the differences between teams were investigated and found to be caused primarily by different conceptual model assumptions (including temperature dependence of the thermal expansion of water), different model formulations (including porosity evolution) and differences in modelled domain sizes, boundary conditions and grid discretisation. This demonstrates that comparisons between multiple modelling teams and/or comparison with analytical results and experimental data are highly beneficial in providing an indication of uncertainty in model predictions. At the conclusion of Step 0, almost all teams had achieved a close agreement in model results and those that had not achieved an agreement knew the reason for this. Step 1 moved from 2D models to 3D models of the FE experiment without adding technical features like shotcrete or EDZ, and only considering the heating phase. Initially the 3D model was tightly specified to continue to build confidence in the model implementations (Step 1a). The results of Step 1a were compared to the data from the FE-experiment without the teams seeing the data. The teams were then provided with a sub-set of the data from the FE-experiment and invited to consider how best to use the large dataset for model comparison (Step 1b). Teams were then asked to use the data provided to calibrate their models, only changing material property values rather than adding features or processes to their models (Step 1c). In Step 1, teams were asked to only model the heating phase of the experiment, so pressure in the Opalinus Clay was reported as change in pressure since the initial conditions were specified rather than modelled. The change from 2D to 3D models was accompanied by an increase in the dispersion of results between the teams. Some of this was resolved during the task, but some remained and is potentially due to model discretisation. Calibration of parameters was useful in improving the fit of the models to the data but the remaining differences indicated that the models were missing features or processes. In Step 2, the teams were asked to update their models with additional features and processes as well as calibrating parameters to try and improve the fit of the models to the data. Teams were encouraged to represent ventilation of the open FE tunnel prior to backfilling with heaters and bentonite and in Step 2, the absolute pressure in the Opalinus Clay was compared between the teams. Teams took different approaches, but there was consideration of adding shotcrete and an EDZ into the model, representing stress change during excavation and different approaches to modelling ventilation of the FE tunnel. Overall, the documented results showed a very good agreement for temperature. The results for porewater pressure evolution showed a significant improvement for most teams compared to Step 1c with a good agreement to the measurements for several teams whereas some teams overpredicted the pressure increase and others overpredicted the drainage effect especially for the sensors close to the heater. Step 3 was an opportunity for teams to use the models developed in Step 1 and Step 2 to make predictions about the temperature and pressure changes that will be expected at the FE experiment over the next few years in light of the planned changes in thermal output of the heaters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

MindSynchro

This report presents the developments and results of MindSynchro project as part of DOE OE FOA 1861. DOE and Pacific Northwest National Laboratory (PNNL) have made available to FOA awardees datasets containing years of real historical data recorded from various phasor measurement units (PMUs) which are installed in three large US interconnections: Texas (IC A), Western (IC B), and Eastern (IC C). The main goal of the project, which was successfully achieved, was to develop methods for detection and identification of events which are relevant for power grid operation. Tasks performed for achieving the project goals included data exploration and pre-processing, the development and application of physics-based features, data analysis and labeling based on unsupervised learning approaches, training and testing of DSSL models for classification of events which are relevant for power grid operation, and deployment of solutions to cloud environments. The methods developed in the project can potentially provide relevant benefits to power grid asset owners/operators in general in terms of situational awareness. Two main types of outcomes can be provided by these tools: Identification of specific relevant power grid event types: Semi-supervised ML methods developed in the project can adequately employ not only the relatively scarce labeled data but also the large amount of available unlabeled data to train models for detection of specific event types. Such methods enable the application of trained models for the detection of events in a population of PMUs much larger than that associated to the labeled events. Support in data labeling / label validation: Labels are critical for training of models for identification of specific types of events. However, labeling large amounts of data is a manual and tedious process. This means that such process is error prone and is not scalable. Methods developed in the project, based on ensembles of clustering models, have been successfully employed for turning manual labeling into a scalable process. Accurate identification of specific relevant events can provide the operators with immediate situational awareness that could otherwise require hours or days of analysis from domain experts. We envision that such methods could be initially employed in support of post-mortem analysis of events and, as confidence is gained, they could be employed for online/real-time support, providing, among other benefits, insights for avoiding major events which could happen due to a combination of smaller ones. On the longer term, related methods could potentially be employed to improve protection and control.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Evaluation of Polyethylene and Blank Pulsed Sphere Experiments Using Deuteron Transport Feature in COG

From the late 1960s to about 1985, LLNL undertook a series of ‘pulsed sphere’ experiments for 31 materials involving 148 different experiments using 75 different spheres. The purpose was to measure the neutron leakage spectra for different materials from 14-MeV neutrons generated by 3 H(d,n) 4 He reactions induced by an incident D+ beam from the Insulated Core Transfer (ICT) accelerator at LLNL. This deuteron beam was focused to impinge upon tritium loaded onto a titanium substrate within a low mass target assembly placed within the center of a spherical shell constructed from the material of interest. COG is a three-dimensional, continuous energy, Monte Carlo code, developed by Lawrence Livermore National Laboratory (LLNL). Recent additions to COG include alpha and deuteron particle transport in order to directly calculate (α,n) and 3 H(d,n) 4 He reactions, and resulting neutron emission spectra. Results of the direct deuteron transport calculation for the 0.8 MFP (mean free path) polyethylene sphere with PILOT B detector was previously published. The purpose of this paper is to present expanded COG results showing the neutron peak from deuterium buildup ( 2 H(d,n) 3 He) due to tritium decay in the target. Cross section data libraries used are ENDF/B-VIII.0 for neutrons and ENDF/B-VII.1 for deuterons, respectively.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

MCNP® Code Version 6.3.2 Theory & User Manual (Rev. 1)

This document acts as a repository of knowledge for the Monte Carlo N-Particle (MCNP) transport computer code. It is maintained alongside the source code and attempts to introduce new users and re-familiarize experienced users with the theory and practices of using the MCNP code for the wide range of particle transport analyses that it is appropriate for. The latest version of the MCNP code, version 6.3.2, provides the Monte Carlo particle transport community with the latest feature developments and bug fixes in the MCNP code. The MCNP code version 6.0 and later is also known as the MCNP6 code.

42 ENGINEERING↗