Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Section III”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14

Assessments of epistemic uncertainty using Gaussian stochastic weight averaging for fluid-flow regression

Here, we use Gaussian stochastic weight averaging (SWAG) to assess the epistemic uncertainty associated with neural-network-based function approximation relevant to fluid flows. SWAG approximates a posterior Gaussian distribution of each weight, given training data, and a constant learning rate. Having access to this distribution, it is able to create multiple models with various combinations of sampled weights, which can be used to obtain ensemble predictions. The average of such an ensemble can be regarded as the 'mean estimation', whereas its standard deviation can be used to construct 'confidence intervals', which enable us to perform uncertainty quantification (UQ) with regard to the training process of neural networks. We utilize representative neural-network-based function approximation tasks for the following cases: (i) a two-dimensional circular-cylinder wake; (ii) the DayMET dataset (maximum daily temperature in North America); (iii) a three-dimensional square-cylinder wake; and (iv) urban flow, to assess the generalizability of the present idea for a wide range of complex datasets. SWAG-based UQ can be applied regardless of the network architecture, and therefore, we demonstrate the applicability of the method for two types of neural networks: (i) global field reconstruction from sparse sensors by combining convolutional neural network (CNN) and multi-layer perceptron (MLP); and (ii) far-field state estimation from sectional data with two-dimensional CNN. We find that SWAG can obtain physically-interpretable confidence-interval estimates from the perspective of epistemic uncertainty. This capability supports its use for a wide range of problems in science and engineering.

97 MATHEMATICS AND COMPUTING↗

Photoionization of Xe 5s: angular distribution and Wigner time delay in the vicinity of the second Cooper minimum

We report the angular distribution and photoionization Wigner time delay of Xe 5s photoelectrons are studied in the region of the second Cooper minimum (SCM) using (i) the relativistic multiconfiguration Tamm–Dancoff approximation, (ii) the relativistic-random-phase approximation (RRPA) and (iii) the RRPA-with-relaxation to demonstrate how differing treatments of correlation, and the relativistic interactions, affect the results. The results of the three methods are compared with each other and with available experimental data. The comparison reveals the importance of electron correlations for which a multiconfiguration description of the initial state is essential. The spin-resolved and spin-averaged photoionization time delay results show important signatures in the region of the SCM in the Xe 5s photoionization cross-section.

74 ATOMIC AND MOLECULAR PHYSICS↗

Jet energy drop

We study the jet energy drop, which is the relative difference between the groomed and ungroomed jet energy or transverse momentum. It is one of the fundamental quantities that characterizes the impact of grooming on jets produced in high energy collisions. We consider three different grooming algorithms i) soft drop, ii) iterated soft drop, and iii) trimming. We carry out the resummation of large logarithms of the jet energy drop, the jet radius as well as relevant grooming parameters at next-to-leading logarithmic (NLL') accuracy. In addition, we account for non-global and clustering logarithms, and determine the next-to-leading order corrections. For soft drop we perform a joint resummation of the jet energy drop and the groomed jet radius, which is necessary to achieve the correct all-order structure of the cross section, in particular for the Sudakov-safe case of soft drop with β = 0. We present numerical results for LHC energies and compare to Pythia simulations as well as CMS data. Our factorization framework predicts the onset of nonperturbative effects in the jet energy distribution, in line with what we find in Pythia. The jet energy drop observables stand out because they only probe soft radiation, making them ideal candidates for the tuning of parton shower Monte Carlo event generators and for probing medium effects in heavy-ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Mechanical Properties and Deformation Behavior of Additively Manufactured 316L Stainless Steel (FY2020)

The Transformational Challenge Reactor (TCR) program plans to build most of the TCR core components through additive manufacturing (AM) processes. These processes include laser powder bed fusion (LPBF) for the metallic (316L) components and the newly developed combined process of binderjet printing and chemical vapor infiltration (CVI) for the SiC fuel matrix. Mechanical testing and characterization tasks have been carried out since the beginning of the TCR program to (1) build a property database for the AM materials that will be used in TCR core and (2) to assess the materials’ performance in TCR-relevant conditions. This document reports the outcome of the testing and characterization efforts for the fiscal year with a focus on the mechanical performance data of AM 316L stainless steel (SS). Baseline tensile testing over a wide temperature range of room temperature–600 °C was completed for the AM 316L alloy in as-built, stress-relieved, and solution-annealed conditions. The as-built 316L showed the highest strength, and the alloy after the post-build treatments showed reduced strengths in the low-strain range. However, the strength differences among the AM materials became insignificant in the later part of deformation. Furthermore, regardless of post-build processing, the AM 316L SS showed higher strength and comparable ductility when compared with wrought 316L SS. Thermal creep testing and microstructural evolution during creep deformation were also performed under selected conditions. It was found that the AM 316L steel showed the best creep resistance in the stress-relieved condition. In-situ tensile tests were performed using scanning electron microscopy and 1-ID beamline at the Advanced Photon Source to elucidate the deformation and fracture behavior of AM 316L and the evolution of crystalline stress, dislocations, and pore distribution. Using these in-situ testing data, an in-depth analysis of the roles of microstructural features in deformation and fracture processes is presented herein. The final section of the document introduces ongoing and future activities for materials testing and characterization, including irradiation effect studies and ball punch testing on AM 316L and AM IN718 alloys.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Thermomechanics coupling to Monte Carlo particle transport on unstructured mesh geometries using Cardinal

Geometry deformation due to thermal expansion influences neutron transport in many systems. Studying this phenomenon involves coupling models for neutronics, thermal hydraulics, and solid mechanics. To enable high fidelity modeling of these coupled physics, new capabilities were introduced in Cardinal, coupling OpenMC Monte Carlo particle transport models with MOOSE thermomechanical physics on unstructured moving-mesh geometries. In this work, we present a fully open-source capability leveraging on-the-fly mesh skinning to automatically regenerate OpenMC geometry, which allows multiphysics feedback from temperature, density, and geometry changes. The new capability is verified using an analytic benchmark slab problem, which couples S 2 neutron transport with thermal conduction, convective boundary conditions, Doppler-broadened cross sections, and nonlinear thermal expansion effects along the heated slab. Cardinal reproduces the analytic solutions for the neutron flux, heating, k eff , and temperature with demonstrated convergence in various error terms including mesh resolution and cross section temperature library spacing. For the nominal benchmark conditions and with a fine mesh, maximum relative errors for neutron flux, temperature, and heating are lower than 1%, while errors in integral quantities such as k eff and slab length are within 1 pcm and 48 µm, respectively. This work (i) presents a new numerical approach to thermomechanics coupling with OpenMC models, (ii) is the first (to our knowledge) to utilize a mechanical partial differential equation (PDE) solution to solve the (Griesheimer and Kooreman, 2022) analytic benchmark, and (iii) develops this verified capability within an open-source package.

97 - MATHEMATICS AND COMPUTING↗

COZMIC. III. Cosmological Zoom-in Simulations of Self-interacting Dark Matter with Suppressed Initial Conditions

We present eight cosmological dark matter (DM)-only zoom-in simulations of a Milky Way–like system that include suppression of the linear matter power spectrum P(k), and/or velocity-dependent DM self-interactions, as the third installment of the COZMIC suite. We consider a model featuring a massive dark photon that mediates DM self-interactions and decays into massless dark fermions. The dark photon and dark fermions suppress linear matter perturbations, resulting in dark acoustic oscillations in P(k), which ultimately affect dwarf galaxy scales. The model also features a velocity-dependent elastic self-interaction between DM particles (SIDM), with a cross section that can alleviate small-scale structure anomalies. For the first time, our simulations test the impact of P(k) suppression on gravothermal evolution in an SIDM scenario that leads to core collapse in (sub)halos with present-day virial masses below ≈10 9 M ⊙ . In simulations with P(k) suppression and self-interactions, the lack of low-mass (sub)halos and the delayed growth of structure reduce the fraction of core-collapsed systems relative to SIDM simulations without P(k) suppression. In particular, P(k) suppression that saturates current warm DM constraints almost entirely erases core collapse in isolated halos. Models with less extreme P(k) suppression produce core collapse in ≈20% of subhalos and ≈5% of isolated halos above 10 8 M ⊙ , and also increase the abundance of extremely low-concentration isolated low-mass halos relative to SIDM. These results reveal a complex interplay between early and late-Universe DM physics, revealing new discovery scenarios in the context of upcoming small-scale structure measurements.

dark matter↗

Statistical tools for a better optical model

Background: Modern statistical tools provide the ability to compare the information content of observables and provide a path to explore which experiments would be most useful to give insight into and constrain theoretical models. Purpose: Here we study three such tools in the context of nuclear reactions with the goal of constraining the optical potential. Method: The three statistical tools examined are (i) the principal component analysis, (ii) the sensitivity analysis based on derivatives, and (iii) the Bayesian evidence. We first apply these tools to a toy-model case, comparing the form of the imaginary part of the optical potential. Then we consider two different reaction observables, elastic angular distributions and polarization data for reactions on 48 Ca and 208 Pb at two different beam energies. Results: For the toy-model case, we find significant discrimination power in the sensitivities and the Bayesian evidence, showing clearly that the volume imaginary term is more useful to describe scattering at higher energies. When comparing between elastic cross sections and polarization data using realistic optical models, sensitivity studies indicate that both observables are roughly equally sensitive but the variability of the optical model parameters is strongly angle dependent. The Bayesian evidence shows some variability between the two observables, but the Bayes factor obtained is not sufficient to discriminate between angular distributions and polarization. Conclusions: From the cases considered, we conclude that, in general, elastic scattering angular distributions have similar impact in constraining the optical potential parameters compared with the polarization data. The angular ranges for the optimum experimental constraints can vary significantly with the observable considered.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Expansion of Machine-Learning Method for Classifying Neutron Resonances

The understanding of astrophysics processes and the performance of nuclear reactors and other nuclear systems depend on a precise description of the neutron interaction cross sections for materials and nuclei present in these environments. At low neutron energies, these cross sections exhibit resonance structure represented by sharp enhancements when the neutron energy is sufficiently close to excited levels in a compound nucleus. Such resonances can be characterized by their quantum numbers relative to angular momenta, which are often deduced in an ad hoc and irreproducible manner from the shape of the cross sections. The correct assignment of the quantum numbers of neutron resonances is therefore of paramount importance. To address this we have developed a machine-learning method to automate the identification and correction of these spin assignments. The algorithm is trained from simulated data, generated from statistical properties of resonance data for a given nucleus, to mimic the errors found in real data. In this project we describe five independent approaches to further develop and expand the applicability of the machine-learning spin classifier: i) Feature impact; ii) Integration with the Atlas; iii) Training optimization; iv) Spacings systematics; and v) Validation with polarized data. The premises, methods, results, and future perspectives are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Fused Deposition Modeling Additive Manufacturing of Carbonized Structures via Waste-Enhanced Filaments

This report details the development, characterization, and use of coal-enhanced composite materials in additive manufacturing applications. High coal loading formulations—containing up to 70 wt.% coal—were successfully extruded and processed using commercially available 3D printers. Extensive experimental testing was conducted to assess the mechanical, thermal, and microstructural properties of the composites. In parallel, multi-scale computational modeling was employed to elucidate atomistic interactions and evaluate the effects of printing-induced defects on structural performance. Large-scale printability trials demonstrated the feasibility of fabricating complex components for tooling and construction applications, including wind turbine blade molds and modular wall sections. Techno-economic analyses demonstrated the cost-effectiveness and scalability of coal-enhanced composites for large-scale additive manufacturing applications such as wind turbine blade tooling.

01 COAL, LIGNITE, AND PEAT↗

Impact of Classical and Quantum Light on Donor–Acceptor–Donor Molecules

Investigations of entangled and classical two-photon absorption have been carried out for six donor (D)–acceptor (A)–donor (D) compounds containing the dithieno pyrrole (DTP) unit as donor and acceptors with systematically varied electronic properties. Comparing ETPA (quantum) and TPA (classical) results reveals that the ETPA cross section decreases with increasing TPA cross section for molecules with highly off-resonant excited states for single-photon excitation. Theory (TDDFT) results are in semiquantitative agreement with this anticorrelated behavior due to the dependence of the ETPA cross section but not TPA on the two-photon excited state lifetime. Furthermore, the largest cross section is found for a DTP derivative that has a single photon excitation energy closest to resonance with half the two-photon excitation energy. These results are important for the possible use of quantum light for low-intensity energy-conversion applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulation of SPND Beta-Current in AP1000 core

The Self-Powered Neutron Detectors (SPNDs) are widely used in Generation-III commercial PWR due to its small size and external-power free character. It can measure the in-core neutron flux density immediately to obtain the power profile in the core. To better understand the actual state of the simulated core, a SPND beta-current simulation module has been established in the NECP-Bamboo code. Firstly, neutron simulation is carried out in the lattice code Bamboo-Lattice together with nuclide depletion simulation to obtain the depleted composition of the entire lattice including the SPND, and the few-group parameters including density and cross section of emitter material. Secondly, the depleted lattice can then be piped into a Monte-Carlo code for neutron-photon-electron simulation to obtain the electron escape efficiency from the emitter of the SPND to the corresponding collector. Thirdly, the electron escape efficiency can be parameterized into the function of the lattice state parameters similarly to the common few-group constants. Finally, the beta-current was calculated by the core code Bamboo-Core simultaneously with the simulation of the core operation process. The beta-current of the Vanadium SPND in the AP1000 core was simulated and analyzed in this paper. Comparison between simulation and measurement of the beta-current distribution in the specific core state is shown in this paper to verify the effectiveness of the method and the code. The radial normalized current distribution is in good agreement with the measurement. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Issue Summary of INL Phase IV Transient Results for IAEA CRP on HTGR UAM Benchmark

This report details the Parallel and Highly Innovative Simulation for Idaho National Laboratory (INL) Code System (PHISICS)/Reactor Excursions and Leak Analysis Program (RELAP5)-3D results obtained for the transient core exercises defined for Phase IV of the International Atomic Energy Agency (IAEA) Coordinated Research Project (CRP) on high-temperature gas cooled reactor (HTGR) uncertainty analysis in modeling (UAM). The Phase III models and results are linked to the earlier Standardized Computer Analyses for Licensing Evaluation (SCALE)/Sampler/New ESC-based Weighting Transport (NEWT) data generated for the lattice physics (lattice) stage Phase I of the CRP. The focus of this report is the Uncertainty/Sensitivity Assessment (U/SA) of the prismatic modular high-temperature gas cooled reactor (MHTGR)-350 design, and specifically for Exercises IV-1 and IV-2 of the benchmark: the Control Rod Withdrawal (CRW) and Pressurised Loss of Cooling (PLOFC) events. The statistical U/SA methodology is implemented and demonstrated using the RAVEN code, based on perturbed cross-section libraries obtained from the SCALE/Sampler sequence. Uncertainties in nuclear data (cross-sections and the average number of neutrons produced per fission, 235U[¯v ]) lead to standard deviations (uncertainties of one s) of approximately 0.5% in the core eigenvalues of the MHTGR-350 and core models. For the coupled neutronics/thermal fluid model, local power density uncertainties up to 3.6% were observed in the colder regions of the core, while the local maximum fuel temperature uncertainties reached 1.5% for the models that included thermal fluid uncertainties. The addition of thermal fluid uncertainties dominated the impacts of nuclear data uncertainties in all cases. The main contributors to uncertainties in the power density and fuel temperatures during the transients were uncertainties in the reactor operating conditions (total power, inlet mass flow rate and inlet gas temperature). Variations in the bypass flows did not have significant impact on any of the output variables. For the nuclear data uncertainties it was found that the 235U(¯v ) / 235U(¯v ) covariance produced the largest sensitivities in terms of its impact on the eigenvalue and peak reactor power. It was also observed that the impact of any nuclear data uncertainties on the maximum fuel temperature was much less significant that the impact on eigenvalue and power. Another important finding was that although the use of eight or more energy groups is recommended for best-estimate HTGR simulation, two-group models produced acceptable uncertainty and sensitivity results for most FOMs. Since the statistical U/SA methodology is computationally expensive, and most transient solver requirements will scale directly with the number of energy groups, two energy groups could be used by HTGR developers during the early stages of design when larger uncertainty margins can be tolerated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Solar Field Layout and Aimpoint Strategy Optimization

The existing methods that determine heliostat aiming strategies for concentrating solar power (CSP) central receiver plants typically use heuristics and/or are computationally expensive, and they lack flexibility for different desired flux profiles and receiver geometries. Because of the interaction between layout and aimpoint strategy, considering the former without accounting for the latter may yield solutions with superfluous heliostats that cannot be used efficiently without compromising receiver flux constraints. To that end, we develop a software decision tool that uses innovative optimization methods to both optimize aimpoint strategies and improve candidate layouts for the solar collection field of a CSP central receiver plant. A CSP plant’s effectiveness relies on the optical efficiency of the solar field, which may be limited by losses due to (i) the cosine effect, (ii) atmospheric attenuation, (iii) interference (i.e., shading and blocking) between heliostats, (iv) spillage as a result of heliostat positioning and geometry, and (iv) some heliostats’ inability to direct irradiance to the receiver without damage due to excessive thermal flux. The goal of this work is to obtain optimized aiming strategies and improved solar field layouts that reduce capital cost and increase field optical efficiency and utilization, while meeting the power requirements of a given CSP receiver design. We formulate the aimpoint optimization problem as a mixed-integer linear programming model, which we then decompose into submodels that we solve in parallel. The decomposition subdivides the solar field into sections, and aimpoint strategies for each section are obtained independently of the others. To improve existing layouts, we develop a utilization-weighted efficiency metric that we use to relocate heliostats to sections of the solar field with similar efficiency and higher utilization. Finally, to connect our software to high-fidelity flux models, we develop a Python application programming interface for SolarPILOT, a mature software package that characterizes solar field performance and generates the heliostat layouts and flux maps that serve as input to our models.

14 SOLAR ENERGY↗

Modeling of transverse stimulated Raman scattering in KDP/DKDP in large-aperture plates suitable for polarization control

Transverse stimulated Raman scattering (TSRS) in potassium dihydrogen phosphate (KDP) and deuterated potassium dihydrogen phosphate (DKDP) plates for large-aperture, inertial confinement fusion (ICF)-class laser systems is a well-recognized limitation giving rise to parasitic energy conversion and laser-induced damage. The onset of TSRS is manifested in plates exposed to the ultraviolet section of the beam. TSRS amplification is a coherent process that grows exponentially and is distributed nonuniformly in the crystal and at the crystal surfaces. To understand the growth and spatial distribution of TSRS energy in various configurations, a modeling approach has been developed to simulate the operational conditions relevant to ICF-class laser systems. Specific aspects explored in this work include (i) the behavior of TSRS in large-aperture crystal plates suitable for third-harmonic generation and use as wave plates for polarization control in current-generation ICF-class laser system configurations; (ii) methods, and their limitations, of TSRS suppression and (iii) optimal geometries to guide future designs.

47 OTHER INSTRUMENTATION↗

Interactive Exploration of High-Dimensional Phase Diagrams

High-dimensional thermodynamic phase stability databases are becoming increasingly common due to the convergence of three recent trends: (i) the widespread interest in so-called “high-entropy” alloys, (ii) the availability of high-throughput computational assessments of phase stability in broad composition spaces and (iii) the ongoing development of ever-increasingly broad, multicomponent, multiphase CALPHAD databases. Although automated computational tools can readily process such high-dimensional data, scientists are often unable to visualize the relevant phase relations, an ability that is crucial to gaining an intuitive understanding of the stability constraints governing materials design. The present work addresses this need by providing algorithms that enable the interactive exploration of phase equilibria in high-dimensional spaces. These algorithms concentrate the complex nonlinear nonsmooth optimization needed into a preprocessing step that generates a large number of high-dimensional yet elementary graphical primitives. Furthermore, these primitives can then be cross-sectioned to yield 3-dimensional views in a computationally efficient manner that enables an interactive exploration of high-dimensional spaces. All of these operations are highly parallelizable, thus facilitating scaling of this method to large data sets.

36 MATERIALS SCIENCE↗

Nimble Feedthrough Qualification - 125% High Explosive Overpressure Test Plan RevA

The primary purpose of this High Explosive (HE) Over-Pressure Test (OPT) is to qualify top cover diagnostic feedthroughs that will be used on LLNL Nimble Subcritical Experiment (SCE) Series designs per experimental design verification requirements specified in ASME Boiler and Pressure Vessel Code Case 2564, Impulsively-Loaded Pressure Vessels, Section VIII, Division 3; and to satisfy the over-test requirement of DOE-STD-1212. The diagnostic feedthroughs are part of the Vessel Confinement System (VCS), which is credited as a Safety Significant Design Feature per the U1a Facility Documented Safety Analysis (DSA). The OPT will be conducted at the LANL Area 1, R306 Firing Site (TA-15-R306) in a 3-foot diameter VCS depicted in Figure 1.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Molecular Vision - Multimodal, multitask retrieval of molecular structure from measured signatures for reference-free compound identification

We are currently at risk of generating false conclusions based on limited methods to identify small molecules in biological systems and in chemical forensics. By definition, the chemical structures of novel small molecules have not been determined, let alone measured or synthesized. Currently, unambiguous structure determination of small molecules is constrained by the time and effort needed to isolate compounds and perform de novo structure elucidation using laboratory-based methods, significantly extending the time to inform mitigation strategies. To address this gap, we have developed a deep learning approach to directly map molecular structure to experimental signatures. We aim to unify measurement technologies employed in untargeted small molecule identification studies—such as infrared (IR) spectrometry, tandem mass spectrometry (MS/MS), ion mobility spectrometry-derived collision cross section (CCS)—through use of a multimodal, multitask deep learning architecture. Where existing methods require direct generation of information-rich spectra and/or properties, an inherently difficult task, we will simplify molecular signature-based identification by posing the problem as a recognition or retrieval task. The model is thus presented with relevant endpoints – structure and one or more molecular signatures – and need only determine whether they are semantically related. Thus, our approach offers the following advantages over existing techniques: (i) circumvents difficulties associated with direct generation of molecular signatures from structure and structure from signatures; (ii) incorporates multiple molecular signatures simultaneously, as available, to support identification; and (iii) enables rapid computation of structural embeddings toward broad coverage of known chemical space. Taken together, the approach removes the need to explicitly obtain or compute reference spectra, representing a powerful method for compound identification that requires only experimentally observed signatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Addendum 2 to the Closure Report for CAU 577 Area 5 Chromium Containing Waste Disposal Cells, NNSS, Nevada

Corrective Action Unit (CAU) 577, “Area 5 Chromium Containing Waste Disposal Cells,” includes five low-level waste cells at the Nevada National Security Site Area 5 Radioactive Waste Management Site where buried waste received from Nuclear Fuel Services, Inc., was subsequently determined to contain chromium that exceeded the toxicity characteristic leaching procedure regulatory limit, which would require the waste to carry hazardous waste code D007. CAU 577 was created to satisfy the requirements of the Settlement Agreement (SA) executed between the Nevada Division of Environmental Protection (NDEP) and the U.S. Department of Energy, National Nuclear Security Administration Nevada Field Office (NNSA/NFO) on April 25, 2019 (NDEP 2019). The SA required that the chromium-containing waste received from NFS would be addressed following the closure process laid out in the Federal Facility Agreement and Consent Order (FFACO). The FFACO process ensures proper closure of the chromium-containing waste and documentation of that closure through FFACO-type documents. The following three Corrective Action Sites (CASs) were closed, and their closure was documented in the Closure Report for Corrective Action Unit 577: Area 5 Chromium Containing Waste Disposal Cells, Nevada National Security Site, Nevada, DOE/EMNV--0030, dated September 2021 (U.S. Department of Energy [DOE] Environmental Management [EM] Nevada Program 2021a): • CAS 05-21-02, Waste Disposal Cell 12 • CAS 05-21-03, Waste Disposal Cell 15 • CAS 05-21-04, Waste Disposal Cell 17 Closure of the following CAS was previously documented in the Addendum to the Closure Report for Corrective Action Unit 577: Area 5 Chromium Containing Waste Disposal Cells, Nevada National Security Site, Nevada, DOE/EMNV--0030-ADD, dated September 2022 (DOE EM Nevada Program 2022): • CAS 05-21-05, Waste Disposal Cell 20 This second addendum to the Closure Report documents the closure activities that have occurred for CAS 05-21-06, Waste Disposal Cell 21. This is the last CAS in CAU 577. The final waste shipment was placed in the waste disposal cell on November 21, 2022. Following this, closure activities began on November 28, 2022, and were conducted according to the Corrective Action Decision Document/Corrective Action Plan (CADD/CAP) for CAU 577 (DOE EM Nevada Program 2021b). The following closure activities were performed: • Constructing an engineered evapotranspiration cover • Installing two subsidence monuments and vadose zone monitoring equipment • Seeding the cover with a mixture of native plant species • Installing four concrete monuments on the corners of the cover and placing two use restriction (UR) warning signs on each monument These activities fulfill applicable federal and state regulations for closure of CAS 05-21-06 and minimize potential future exposure pathways to buried waste. Completed closure activities are also consistent with closure of the nine historical Resource Conservation and Recovery Act (RCRA) units included in Section 10.2.2 of the RCRA Permit that governs hazardous waste management activities at the Nevada National Security Site (Permit NEV HW0101) (NDEP 2023). UR documentation for this CAS is included in Appendix B of this report. The post-closure plan is presented in detail in the CADD/CAP for CAU 577 (DOE EM Nevada Program 2021b), and the requirements are summarized in Section 5.2 of this document. In accordance with paragraph 5D of the SA, a request to incorporate the requirements for post-closure monitoring of CAU 577 was included with the permit application for RCRA Permit NEV HW0101 that was submitted in January 2022 (NNSA/NFO 2022). The request included the post-closure requirements for the three CASs that had been closed at the time of submittal of the application as well as requirements that would be implemented upon future approval of closure of the remaining two CASs. All CAU 577 post-closure monitoring requirements have been captured in the April 4, 2023, Revision 7 of the RCRA Permit (NDEP 2023). As the RCRA Permit NEV HW0101 has been revised since the submittal of the original CAU 577 Closure Report (DOE EM Nevada Program 2021a) and Addendum 1 (DOE EM Nevada Program 2022), the post-closure requirements in this Addendum 2 report do not align with the previous documents. Specific changes resulting from the issuance of Revision 7 of the RCRA Permit are discussed in Section 5.2 of this report. The requirements in this report are consistent with the current permit (NDEP 2023) and supersede all requirements listed in the CAU 577 Closure Report and Addendum 1. All CAU 577 post-closure requirements should be conducted in accordance with the version of the RCRA Permit that is current at the time of the activities being performed. The DOE EM Nevada Program is requesting a Notice of Completion from NDEP for closure of CAU 577. Although CAU 577 is not a legacy site, the FFACO process is being followed to ensure proper closure of the chromium-containing waste. Therefore, transfer of CAU 577 from Appendix III of the FFACO to Appendix IV, Closed Corrective Action Units, is requested, as all closure activities have been completed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗