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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Application of a Novel DCPD Adjustment Method for the J-R Curve Characterization: A study based on ORNL and ASTM Interlaboratory Results

Material fracture toughness in the fully ductile region can be described by a J-integral vs. crack growth resistance curve (J-R curve). As a conventional J-R curve measurement method, the elastic unloading compliance (EUC) method becomes impractical for elevated temperature testing due to relaxation of the material and friction induced back-up shape of the J-R curve. One alternative solution of J-R curve testing applies the Direct Current Potential Drop (DCPD) technique for measuring crack extension. However, besides crack growth, potential drop can also be influenced by plastic deformation, crack tip blunting, etc., and uncertainties exist in the current DCPD methodology especially in differentiating potential drop due to stable crack growth and due to material deformation. Thus, using DCPD for J-R curve determination remains a challenging task. In this study, a new adjustment procedure for applying DCPD to derive the J-R curve has been developed for conventional fracture toughness specimens, including compact tension, three-point bend, and disk-shaped compact specimens. Data analysis has been performed on Oak Ridge National Laboratory (ORNL) and American Society for Testing and Materials (ASTM) interlaboratory results covering different specimen thicknesses, test temperatures, and materials, to evaluate the applicability of the new DCPD adjustment procedure for J-R curve characterization. After applying the newly-developed procedure, direct comparison between the DCPD method and the normalization method on the same specimens indicated close agreement for the overall J-R curves, as well as the provisional values of fracture toughness near the onset of ductile crack extension, Jq, and of tearing modulus.

DCPD↗
DOE OSTI2020

Technology Development for Dry Storage of Aluminum-Clad Spent Nuclear Fuel - 20490

A candidate disposition pathway for the > 13 MTHM of aluminum-clad spent nuclear fuel (ASNF), owned and managed by the U.S. Department of Energy, is the drying and placement of the SNF into sealed-canister dry storage, with the ASNF-in- canisters 'road-ready' for transportation to and final direct disposal in a repository waste package. Technical information gaps in fuel drying, and fuel dry storage behavior, have previously challenged the declaration of technology readiness for drying and placement of this fuel into the DOE Standard Canister design for > 50 years of safe dry storage. The principal technical information gaps included: i) characterization and thermal dehydration behavior of aluminum (oxy)hydroxide films attendant on the cladding due to film formation during reactor operation and during post-discharge up to long-term wet storage histories; and ii) G-value data to enable estimation of the radiolytic gas generation from the cladding with its (oxy)hydroxide films. Thus, the oxide films on the ASNF challenged the safety of a sealed storage canister with thermal and radiolytic decomposition of the waters on the films that can lead to corrosion, pressurization, and flammability issues. These gaps in the technical information base have largely been closed. This paper discusses the investigations at the Idaho National Laboratory (INL) and the Savannah River National laboratory (SRNL), and outlines the pending technology development work for input to an engineering design to enable a road-ready dry storage system for ASNF. The ASNF inventory considered for road-ready dry storage is stored at the Savannah River Site (SRS) and at the Idaho Nuclear Technology and Engineering Center (INTEC) at the INL. The ASNF inventory in the SRS L Basin is from foreign and domestic research reactors (FRR and DRR), and is diverse in terms of design, irradiation, and post-reactor-discharge storage conditions; these factors yield a range of characteristics of cladding oxide films on ASNF. Mixed aluminum (oxy)hydroxide (boehmite and bayerite/gibbsite) films, non-uniform in thicknesses up to a maximum local thickness bounded by 25 μm, were observed on ASNF materials removed from wet storage in the L Basin and in non-sealed dry storage at the SRS following reactor service and a long-term (up to 40+ years) interim storage history. The ASNF inventory at INTEC, in both wet and vented dry storage, is predominantly from the Advanced Test Reactor (ATR), but it also includes DRR and FRR fuel. To address a profound behavior of these films, radiolysis testing of aluminum specimens with mixed type boehmite/bayerite oxide films was performed to develop basic data on G-values for production of radiolytic hydrogen under dry storage conditions with nominal relative humidity, temperature, and cover gas. Modeling and simulation of canister internal environments with postulated inventories of oxide films provides estimation of the evolution of the conditions of the canister loaded with ASNF. Simultaneous Thermal Analysis (TGA/DSC) of hydrated oxide powders, and laboratory-scale aluminum specimens with a bayerite film (∼10 μm) using TGA methods, inform drying time/temperature conditions to be used for the ASNF. A demonstration project is recommended for Verification and Validation of the drying and storage of the ASNF. Remaining major tasks leading up to the hot demonstration include scale-up radiolysis testing and scale-up drying testing. Engineering design with the information from the technology program will establish the safety basis and enable long-term (> 50 years) dry storage compatibility with ASNF in the DOE Standard Canister pending its transportation to and disposal in a repository. This full capability would show the ASNF-in-canister storage system to be road-ready. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2011

A Roadmap for NEAMS Capability Transfer

The vision of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program is to bring truly predictive modeling and simulation (M&S) capabilities to the nuclear engineering community in order to enable a new approach to the design and analysis of nuclear energy systems. From its inception, the NEAMS program has always envisioned a broad user base for its software and scientific products, including researchers within the DOE complex, nuclear industry technology developers and vendors, and operators. However activities to date have focused almost exclusively on interactions with NEAMS sponsors, who are also near-term users of NEAMS technologies. The task of the NEAMS Capability Transfer (CT) program element for FY2011 is to develop a comprehensive plan to support the program's needs for user outreach and technology transfer. In order to obtain community input to this plan, a 'NEAMS Capability Transfer Roadmapping Workshop' was held 4-5 April 2011 in Chattanooga, TN, and is summarized in this report. The 30 workshop participants represented the NEAMS program, the DOE and industrial user communities, and several outside programs. The workshop included a series of presentations providing an overview of the NEAMS program and presentations on the user outreach and technology transfer experiences of (1) The Advanced Simulation and Computing (ASC) program, (2) The Standardized Computer Analysis for Licensing Evaluation (SCALE) project, and (3) The Consortium for Advanced Simulation of Light Water Reactors (CASL), followed by discussion sessions. Based on the workshop and other discussions throughout the year, we make a number of recommendations of key areas for the NEAMS program to develop the user outreach and technology transfer activities: (1) Engage not only DOE, but also industrial users sooner and more often; (2) Engage with the Nuclear Regulatory Commission to facilitate their understanding and acceptance of NEAMS approach to predictive M&S; (3) Place requirements gathering from prospective users on a more formal footing, updating requirements on a regular basis and incorporate them into planning and execution of the project in a traceable fashion; (4) Seek out the best available data for validation purposes, and work with experimental programs to design and carry out new experiments that satisfy the need for data suitable for validation of high-fidelity M&S codes; (5) Develop and implement program-wide plans and policies for export control, licensing, and distribution of NEAMS software products; (6) Establish a program of sponsored alpha testing by experienced users in order to obtain feedback on NEAMS codes; (7) Provide technical support for NEAMS software products; (8) Develop and deliver documentation, tutorial materials, and live training classes; and (9) Be prepared to support outside users who wish to contribute to the codes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Computationally efficient characterization of potential energy surfaces based on fingerprint distances

An analysis of the network defined by the potential energy minima of multi-atomic systems and their connectivity via reaction pathways that go through transition states allows us to understand important characteristics like thermodynamic, dynamic, and structural properties. Unfortunately computing the transition states and reaction pathways in addition to the significant energetically low-lying local minima is a computationally demanding task. We here introduce a computationally efficient method that is based on a combination of the minima hopping global optimization method and the insight that uphill barriers tend to increase with increasing structural distances of the educt and product states. This method allows us to replace the exact connectivity information and transition state energies with alternative and approximate concepts. Without adding any significant additional cost to the minima hopping global optimization approach, this method allows us to generate an approximate network of the minima, their connectivity, and a rough measure for the energy needed for their interconversion. This can be used to obtain a first qualitative idea on important physical and chemical properties by means of a disconnectivity graph analysis. Besides the physical insight obtained by such an analysis, the gained knowledge can be used to make a decision if it is worthwhile or not to invest computational resources for an exact computation of the transition states and the reaction pathways. Furthermore it is demonstrated that the here presented method can be used for finding physically reasonable interconversion pathways that are promising input pathways for methods like transition path sampling or discrete path sampling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Mass and galaxy distributions of four massive galaxy clusters from Dark Energy Survey Science Verification data

We measure the weak lensing masses and galaxy distributions of four massive galaxy clusters observed during the Science Verification phase of the Dark Energy Survey (DES). This pathfinder study is meant to (1) validate the Dark Energy Camera (DECam) imager for the task of measuring weak lensing shapes, and (2) utilize DECam's large field of view to map out the clusters and their environments over 90 arcmin. We conduct a series of rigorous tests on astrometry, photometry, image quality, point spread function (PSF) modelling, and shear measurement accuracy to single out flaws in the data and also to identify the optimal data processing steps and parameters. We find Science Verification data from DECam to be suitable for the lensing analysis described in this paper. The PSF is generally well behaved, but the modelling is rendered difficult by a flux-dependent PSF width and ellipticity. We employ photometric redshifts to distinguish between foreground and background galaxies, and a red-sequence cluster finder to provide cluster richness estimates and cluster-galaxy distributions. By fitting Navarro-Frenk-White profiles to the clusters in this study, we determine weak lensing masses that are in agreement with previous work. For Abell 3261, we provide the first estimates of redshift, weak lensing mass, and richness. In addition, the cluster-galaxy distributions indicate the presence of filamentary structures attached to 1E 0657-56 and RXC J2248.7-4431, stretching out as far as 1. (approximately 20 Mpc), showcasing the potential of DECam and DES for detailed studies of degree-scale features on the sky.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Automated Grain Boundary (GB) Segmentation and Microstructural Analysis in 347H Stainless Steel Using Deep Learning and Multimodal Microscopy

Austenitic 347H stainless steel offers superior mechanical properties and corrosion resistance required for extreme operating conditions such as high temperature. The change in microstructure due to composition and process variations is expected to impact material properties. Identifying microstructural features such as grain boundaries thus becomes an important task in the process-microstructure-properties loop. Applying convolutional neural network (CNN)-based deep learning models is a powerful technique to detect features from material micrographs in an automated manner. In contrast to microstructural classification, supervised CNN models for segmentation tasks require pixel-wise annotation labels. However, manual labeling of the images for the segmentation task poses a major bottleneck for generating training data and labels in a reliable and reproducible way within a reasonable timeframe. Microstructural characterization especially needs to be expedited for faster material discovery by changing alloy compositions. Here, in this study, we attempt to overcome such limitations by utilizing multimodal microscopy to generate labels directly instead of manual labeling. We combine scanning electron microscopy images of 347H stainless steel as training data and electron backscatter diffraction micrographs as pixel-wise labels for grain boundary detection as a semantic segmentation task. The viability of our method is evaluated by considering a set of deep CNN architectures. We demonstrate that despite producing instrumentation drift during data collection between two modes of microscopy, this method performs comparably to similar segmentation tasks that used manual labeling. Additionally, we find that naïve pixel-wise segmentation results in small gaps and missing boundaries in the predicted grain boundary map. By incorporating topological information during model training, the connectivity of the grain boundary network and segmentation performance is improved. Finally, our approach is validated by accurate computation on downstream tasks of predicting the underlying grain morphology distributions which are the ultimate quantities of interest for microstructural characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Regularization via f -Divergence: An Application to Multi-Oxide Spectroscopic Analysis

In this paper, we explore the application of convolutional neural networks (CNNs) for predicting the chemical composition of complex geologic samples in a simulated Martian atmospheric environment. Specifically, we aim to characterize oxide weight percentages (wt.%) of rock samples analyzed by remote Laser-Induced Breakdown Spectroscopy (LIBS), framing the problem as a multi-target regression task . Neural networks trained on LIBS spectra are prone to overfitting due to high spectral complexity, limited labeled data, and measurement noise. While regularization is critical for improving generalization, common methods (e.g., ℓ 2 regularization) impose constraints not directly tied to data distribution properties. We propose a novel regularization method based on a specific ƒ-divergence induced by a graph-based estimator, designed to constrain the distributional discrepancy between predictions and targets. This regularizer serves a dual purpose: (a) mitigating overfitting by enforcing a constraint on the distributional difference between predictions and noisy targets, and (b) acting as an auxiliary loss that penalizes large divergences. To enable backpropagation, we develop a differentiable approximation of this particular ƒ-divergence, making the method feasible for neural networks. Experiments on ChemCam and SuperCam LIBS calibration spectra show that mathematical equation-divergence regularization outperforms or matches standard regularization methods (ℓ 1 , ℓ 2 , dropout) and the classical baseline, partial least squares (PLS). Combining ƒ-divergence regularization with standard regularization yields further performance gains, indicating that distributional regularization is useful in this context giving a promising direction for robust model training in planetary science applications. Source code is publicly available at Klein and Li (2025), https://doi.org/10.11578/dc.20250530.7.

58 GEOSCIENCES↗
DOE OSTI2022

Utilization of the Critic Subnetwork of a Generative Adversarial Network as Detector of Morphological Material Change in Image Data

The resolution of computed tomography (CT) has become high enough to monitor morphological changes due to aging in materials in long-term applications. For this work, we explored the utility of the critic of a generative adversarial network (GAN) to automatically detect such changes. The GAN was trained with images of pristine Pharmatose, which is used as a surrogate energetic material. It is important to note that images of the material with altered morphology were only used during the test phase. The GAN-generated images reproduced the microstructure of Pharmatose well, although some unrealistic particle fusion was seen. Calculated morphological metrics (volume fraction, interfacial line length, and local thickness) for the synthetic images also showed good agreement with the training data, albeit with signs of mode collapse in the interfacial line length. While the critic exposed changes in particle size, it showed limited ability to distinguish images by particle shape. The detection of shape differences was also a more challenging task for the selected morphological metrics that related to energetic material performance. We further tested the critic with images of aged Pharmatose. Subtle changes due to aging are difficult for the human analyst to detect; but both critic and morphological metrics analysis showed image differentiation.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Detecting dynamic causal inference in nonlinear two-phase fracture flow

Identifying dynamic causal inference involved in flow and transport processes in complex fractured-porous media is generally a challenging task, because nonlinear and chaotic variables may be positively coupled or correlated for some periods of time, but can then become spontaneously decoupled or non-correlated. In his 2002 paper (Faybishenko, 2002), the author performed a nonlinear dynamical and chaotic analysis of time-series data obtained from the fracture flow experiment conducted by Persoff and Pruess (1995), and, based on the visual examination of time series data, hypothesized that the observed pressure oscillations at both inlet and outlet edges of the fracture result from a superposition of both forward and return waves of pressure propagation through the fracture. In the current paper, the author explores an application of a combination of methods for detecting nonlinear chaotic dynamics behavior along with the multivariate Granger Causality (G-causality) time series test. Based on the G-causality test, the author infers that his hypothesis is correct, and presents a causation loop diagram of the spatial-temporal distribution of gas, liquid, and capillary pressures measured at the inlet and outlet of the fracture. The causal modeling approach can be used for the analysis of other hydrological processes, for example, infiltration and pumping tests in heterogeneous subsurface media, and climatic processes, for example, to find correlations between various meteorological parameters, such as temperature, solar radiation, barometric pressure, etc.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Prospects for constraining the shape of non-Gaussianity with the scale-dependent bias

We consider whether the non-Gaussian scale-dependent halo bias can be used not only to constrain the local form of non-Gaussianity but also to distinguish among different shapes. In particular, we ask whether it can constrain the behavior of the primordial three-point function in the squeezed limit where one of the momenta is much smaller than the other two. This is potentially interesting since the observation of a three-point function with a squeezed limit that does not go like the local nor equilateral templates would be a signal of non-trivial dynamics during inflation. To this end we use the quasi-single field inflation model of Chen and Wang [1, 2] as a representative two-parameter model, where one parameter governs the amplitude of non-Gaussianity and the other the shape. We also perform a model-independent analysis by parametrizing the scale-dependent bias as a power-law on large scales, where the power is to be constrained from observations. We find that proposed large-scale structure surveys (with characteristics similar to the dark energy task force stage IV surveys) have the potential to distinguish among the squeezed limit behavior of different bispectrum shapes for a wide range of fiducial model parameters. Thus the halo bias can help discriminate between different models of inflation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

A domain-specific compiler for a parallel multiresolution adaptive numerical simulation environment

This paper describes the design and implementation of a layered domain-specific compiler to support MADNESS---Multiresolution ADaptive Numerical Environment for Scientific Simulation. MADNESS is a high-level software environment for the solution of integral and differential equations in many dimensions, using adaptive and fast harmonic analysis methods with guaranteed precision. MADNESS uses k-d trees to represent spatial functions and implements operators like addition, multiplication, differentiation, and integration on the numerical representation of functions. The MADNESS runtime system provides global namespace support and a task-based execution model including futures. MADNESS is currently deployed on massively parallel supercomputers and has enabled many science advances. Due to the highly irregular and statically unpredictable structure of the k-d trees representing the spatial functions encountered in MADNESS applications, only purely runtime approaches to optimization have previously been implemented in the MADNESS framework. This paper describes a layered domain-specific compiler developed to address some performance bottlenecks in MADNESS. The newly developed static compile-time optimizations, in conjunction with the MADNESS runtime support, enable significant performance improvement for the MADNESS framework.

Rajbhandari, Samyam↗
DOE OSTI2016

SU-F-P-49: Comparison of Mapcheck 2 Commission for Photon and Electron Beams

Purpose: We will investigate the performance variation of the MapCheck2 detector array with different array calibration and dose calibration pairs from different radiation therapy machine. Methods: A MapCheck2 detector array was calibrated on 3 Elekta accelerators with different energy of photon (6 MV, 10 MV, 15 MV and 18 MV) and electron (6 MeV, 9 MeV, 12 MeV, 15 MeV, 18 MeV and 20 MeV) beams. Dose calibration was conducted by referring a water phantom measurement following TG-51 protocol and commission data for each accelerator. A 10 cm × 10 cm beam was measured. This measured map was morphed by applying different calibration pairs. Then the difference was quantified by comparing the doses and similarity using gamma analysis of criteria (0.5 %, 0 mm). Profile variation was evaluated on a same dataset with different calibration pairs. The passing rate of an IMRT QA planar dose was calculated by using 3 mm and 3% criteria and compared with respect to each calibration pairs. Results: In this study, a dose variation up to 0.67% for matched photons and 1.0% for electron beams is observed. Differences of flatness and symmetry can be as high as 1% and 0.7% respectively. Gamma analysis shows a passing rate ranging from 34% to 85% for the standard 10 × 10 cm field. Conclusion: Our work demonstrated that a customized array calibration and dose calibration for each machine is preferred to fulfill a high standard patient QA task.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

TCF Base Technology-Specific: Real-time soil core scanner for carbon and other elements (Final Report)

The aim of this project was to commercialize an instrument that will accurately and precisely measure carbon in soil, providing a breakthrough in scalable soil core analysis and enabling a robust measurement of the total amount of carbon per acre. The instrument will measure the whole soil core, rather than just a few sub-samples, and provide data for carbon depth profiling, as well as other key soil elements such as Al, Si, O, Fe. This instrument will provide faster turnaround times and more precise results than current methods (such as loss on ignition), facilitating the analysis of many soil cores per acre. Ultimately, this will enable farmers to improve their carbon-in-soil content, thus contributing to an improved soil health and product yield. To achieve this goal, we divided the project into three main tasks: 1) commercialization research, 2) technical development, and 3) instrument development, demonstration, and benchmarking.

47 OTHER INSTRUMENTATION↗
DOE OSTI2011

Linux-Based Software Control for Xenon Systems

This paper will review software control solutions for systems requiring automated control and analysis. Written in the C++ language under the Linux operating system (OS), a client/server architecture was developed for automated systems enabling modularized processes to perform system control. In this scheme, narrowly focused clients and servers communicate with each other to perform tasks necessary for system execution. Each hardware interface, such as analog input/output modules, instrumentation, and detectors, have a server associated with it that can be accessed individually with various client interface programs. These servers also inherently support reporting all sensor values to a state-of-health server. One advantage to this software architecture is that all software servers can be accessed and altered independently without stopping the entire control system providing flexibility during development and operation. Automation is achieved using a state-machine based control program that implements the process necessary to run the system. The state-machine provides a well-defined process flow with each state defining one step in the overall control process. The state-machine framework is highly flexible. During development, states can easily be modified, added, or removed as needed.

Suarez, Reynold↗
DOE OSTI2023

Towards Lightweight Data Integration Using Multi-Workflow Provenance and Data Observability

Modern large-scale scientific discovery requires multidisciplinary collaboration across diverse computing facilities, including High Performance Computing (HPC) machines and the Edge-to-Cloud continuum. Integrated data analysis plays a crucial role in scientific discovery, especially in the current AI era, by enabling Responsible AI development, FAIR, Reproducibility, and User Steering. However, the heterogeneous nature of science poses challenges such as dealing with multiple supporting tools, cross-facility environments, and efficient HPC execution. Building on data observability, adapter system design, and provenance, we propose MIDA: an approach for lightweight runtime Multi-workflow Integrated Data Analysis. MIDA defines data observability strategies and adaptability methods for various parallel systems and machine learning tools. With observability, it intercepts the dataflows in the background without requiring instrumentation while integrating domain, provenance, and telemetry data at runtime into a unified database ready for user steering queries. We conduct experiments showing end-to-end multi-workflow analysis integrating data from Dask and MLFlow in a real distributed deep learning use case for materials science that runs on multiple environments with up to 276 GPUs in parallel. We show near-zero overhead running up to 100,000 tasks on 1,680 CPU cores on the Summit supercomputer.

Santos Souza, Renan↗
DOE OSTI2018

Decontamination and Decommissioning Activities of a Radiopharmaceuticals Production Facility - 18067

On May 2012, Best Medical Belgium S.A. (BMB), a manufacturer of pharmaceutical products located on the nuclear site of Fleurus, was declared bankrupt. According to the Belgian law, ONDRAF/NIRAS (Belgian Radioactive Waste Management Agency) was entrusted with the clean-up and decommissioning operations of the former BMB facilities, nowadays known as 'ONDRAF Site Fleurus' (ONSF). In June 2015, ONSF launched a Decontamination and Decommissioning (D and D) program, for which Tractebel: - Supports the definition of the clean-up and decommissioning strategies; - Drafts the Final Decommissioning Plan (FDP) and Safety Analysis Report (SAR) that will be submitted to FANC/AFCN (Belgian Federal Agency for Nuclear Control) in order to get the License for decommissioning; - Drafts the technical specifications of the public tendering process related to the D and D program; - Ensures the day to-day follow-up of the D and D activities on site. Four nuclear buildings are part of the D and D activities. One of them, building 14 (B14), represents the most challenging and extensive task with the clean-up of highly contaminated areas and its further decommissioning up to the final state. This building features two cyclotrons (CGR and IBA cyclotrons) successively used to produce radioisotopes, as well as hot cells and glove boxes used for their purification and the conditioning of the final pharmaceutical product. The present paper aims at presenting the most recent development steps of the clean-up phase regarding the adaptations of existing facilities and the upcoming activities in preparation of the decommissioning activities. To allow the sorting and the treatment of the radioactive material identified in the physical and radiological inventory, several workshops have been implemented within the B14 building in order to deal with radioactive materials arising from the clean-up and D and D activities. Following the conceptual design phase, Tractebel has actively monitored the on-site activities for the construction of those workshops such as: - The modification of the civil works; - The revamping of the ventilation system; - The installation of dedicated lifting equipment and workstations equipped with cutting devices; - The assembly of a docking station for filling the radioactive packages. The removal of the activated concrete surrounding the IBA cyclotron requires the erection of a containment structure and an extension structure. The containment structure, composed of light metallic beams, is located above the cyclotron and its irradiation zones. For operational security reasons and working efficiency, the cutting process of the concrete ceilings and walls will be performed from the top inside the containment structure by means of an eight tons overhead bridge crane. Concrete blocks resulting from the cutting process will then be lifted, without any loss of containment, towards the extension zone of the nuclear zone of the IBA cyclotron for further resizing, sorting and evacuation towards the identified waste routes. To prepare this task which will be performed during the decommissioning phase, Tractebel sets up the necessary technical specifications. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

2014-2018 Summary of NCAR activities in the Earth Energy Exascale System Model (E3SM) project

NCAR participation in E3SM activities as part of this funded collaborative project has been successful in leveraging the existing atmosphere model development experience from CESM scientists and applying it to initial v1 atmosphere model (EAM) development and analysis. NCAR partners collectively had many decades of experience in parameterization development, running and tuning coupled models and building the required software infrastructure to support ongoing model developments. Furthermore, collaboration between E3SM and CESM developers was of mutual benefit to both modeling endeavors. In the earlier periods of the project, participation in E3SM both complemented core critical path DOE activities and advanced individual parameterization development; including orographic drag, convection parameterization, convective gustiness and cloud and microphysical processes. Significant progress has been made implementing model capabilities for separating out the physics and dynamics grids, and providing the infrastructure for including orographic elevation class communication between the land and atmosphere models. Our activities working with the E3SM workflow and software engineering teams have established efficient protocols and infrastructure for the sharing of CESM and E3SM model codes of interest to both modeling groups, a large component of which is the mutual communication of common code bugs. As well as these specific project tasks all NCAR project members have been regular participants in atmosphere and coupled group telecons, as well as PI meetings. We have been fully engaged with and contributed to decisions regarding v1 atmosphere model developments, coupled model simulations, model tunings, and software engineering infrastructure. NCAR’s contribution to more recent E3SM development activities has centered on analysis of v1 release and pre-release simulations in order to address outstanding systematic biases and communicate climate improvements. Of particularly note is the work in understanding clouds and cloud feedbacks, shortcomings in ENSO and sub-seasonal variability; in particular the Madden Julian Oscillation (MJO). Contributions have been made to a number of papers that are currently published or in preparation detailing model performance in CMIP6-protocal experiments. They outline the simulations of mean climate, clouds and convection processes, convective gustiness, atmospheric blocking coupled climates. The contributions of NCAR’s funded activities to the E3SM atmosphere in the initial years of the project have had a positive impact on many aspects of the model simulations described in these papers.

58 GEOSCIENCES↗
DOE OSTI2017

Synthesis and analysis of separation networks for the recovery of intracellular chemicals generated from microbial-based conversions

Background. Bioseparations can contribute to more than 70% in the total production cost of a bio-based chemical, and if the desired chemical is localized intracellularly, there can be additional challenges associated with its recovery. Based on the properties of the desired chemical and other components in the stream, there can be multiple feasible options for product recovery. These options are composed of several alternative technologies, performing similar tasks. The suitability of a technology for a particular chemical depends on (1) its performance parameters, such as separation efficiency; (2) cost or amount of added separating agent; (3) properties of the bioreactor effluent (e.g., biomass titer, product content); and (4) final product specifications. Our goal is to first synthesize alternative separation options and then analyze how technology selection affects the overall process economics. To achieve this, we propose an optimization-based framework that helps in identifying the critical technologies and parameters. Results. We study the separation networks for two representative classes of chemicals based on their properties. The separation network is divided into three stages: cell and product isolation (stage I), product concentration (II), and product purification and refining (III). Each stage exploits differences in specific product properties for achieving the desired product quality. The cost contribution analysis for the two cases (intracellular insoluble and intracellular soluble) reveals that stage I is the key cost contributor (>70% of the overall cost). Further analysis suggests that changes in input conditions and technology performance parameters lead to new designs primarily in stage I. Conclusions. The proposed framework provides significant insights for technology selection and assists in making informed decisions regarding technologies that should be used in combination for a given set of stream/product properties and final output specifications. Additionally, the parametric sensitivity provides an opportunity to make crucial design and selection decisions in a comprehensive and rational manner. This will prove valuable in the selection of chemicals to be produced using bioconversions (bioproducts) as well as in creating better bioseparation flow sheets for detailed economic assessment and process implementation on the commercial scale.

09 BIOMASS FUELS↗