Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Batch processing”

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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Solution scattering at the Life Science X-ray Scattering (LiX) beamline

This work reports the instrumentation and software implementation at the Life Science X-ray Scattering (LiX) beamline at NSLS-II in support of biomolecular solution scattering. For automated static measurements, samples are stored in PCR tubes and grouped in 18-position sample holders. Unattended operations are enabled using a six-axis robot that exchanges sample holders between a storage box and a sample handler, transporting samples from the PCR tubes to the X-ray beam for scattering measurements. The storage box has a capacity of 20 sample holders. At full capacity, the measurements on all samples last for ∼9 h. For in-line size-exclusion chromatography, the beamline-control software coordinates with a commercial high-performance liquid chromatography (HPLC) system to measure multiple samples in batch mode. The beamline can switch between static and HPLC measurements instantaneously. In all measurements, the scattering data span a wide q -range of typically 0.006–3.2 Å −1 . Functionalities in the Python package py4xs have been developed to support automated data processing, including azimuthal averaging, merging data from multiple detectors, buffer scattering subtraction, data storage in HDF5 format and exporting the final data in a three-column text format that is acceptable by most data analysis tools. These functionalities have been integrated into graphical user interfaces that run in Jupyter notebooks, with hooks for external data analysis software.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules

Abstract Graph Convolutional Neural Network (GCNN) is a popular class of deep learning (DL) models in material science to predict material properties from the graph representation of molecular structures. Training an accurate and comprehensive GCNN surrogate for molecular design requires large-scale graph datasets and is usually a time-consuming process. Recent advances in GPUs and distributed computing open a path to reduce the computational cost for GCNN training effectively. However, efficient utilization of high performance computing (HPC) resources for training requires simultaneously optimizing large-scale data management and scalable stochastic batched optimization techniques. In this work, we focus on building GCNN models on HPC systems to predict material properties of millions of molecules. We use HydraGNN, our in-house library for large-scale GCNN training, leveraging distributed data parallelism in PyTorch. We use ADIOS, a high-performance data management framework for efficient storage and reading of large molecular graph data. We perform parallel training on two open-source large-scale graph datasets to build a GCNN predictor for an important quantum property known as the HOMO-LUMO gap. We measure the scalability, accuracy, and convergence of our approach on two DOE supercomputers: the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) and the Perlmutter system at the National Energy Research Scientific Computing Center (NERSC). We present our experimental results with HydraGNN showing (i) reduction of data loading time up to 4.2 times compared with a conventional method and (ii) linear scaling performance for training up to 1024 GPUs on both Summit and Perlmutter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Modeling Molten Salt Reactor Fission Product Removal with SCALE

Liquid-fuel Molten Salt Reactors (MSRs) allow for continuous online fuel treatment and processing using a variety of subsystems. Among these subsystems, the off-gas system (OGS) continuously removes fission products from the primary fuel salt through a helium sparging process. Accurately modeling fission product behavior is paramount for the development of MSRs; while there are a variety of depletion modeling and simulation tools that allow for removal of material from a defined system, most of them work in a semicontinuous, batch-wise manner. The new tools implemented into TRITON, in the SCALE suite for reactor analysis and design, aim to address this issue by implementing truly continuous material feeds and removals. In addition, material accountancy is enhanced in these tools, which enable tracking of removed material in user-specified mixtures. These continuous depletion tools provide a way to model material transport throughout systems more efficiently and accurately. This report validates the new SCALE MSR modeling capabilities using data from the Molten Salt Reactor Experiment (MSRE). After a framework was established for deriving realistic removal rates based on design specifications, these rates were used by TRITON to continuously remove specific elements while performing burnup calculations. Results were compared to those obtained in MSRE, with a focus on the 135 Xe poison fraction. After these capabilities were validated, the learned concepts and best practices were applied to model the Molten Salt Breeder Reactor (MSBR) and the Molten Salt Demonstration Reactor (MSDR) to study the effects of continuous fission product removal in fuel salt reactivity, as well as the lifetime effects.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Development of ultra-pure gadolinium sulfate for the Super-Kamiokande gadolinium project

This paper reports the development and detailed properties of about 13 metric tons of gadolinium sulfate octahydrate, Gd 2 (SO 4 ) 3 • 8H 2 O⁠, which has been dissolved into Super-Kamiokande (SK) in the summer of 2020. We evaluate the impact of radioactive impurities in Gd 2 (SO 4 ) 3 • 8H 2 O on diffuse supernova neutrino background searches and solar neutrino observation and confirm the need to reduce radioactive and fluorescent impurities by about three orders of magnitude from commercially available high-purity Gd 2 (SO 4 ) 3 • 8H 2 O⁠. In order to produce ultra-high-purity Gd 2 (SO 4 ) 3 • 8H 2 O, we have developed a method to remove impurities from gadolinium oxide, Gd 2 O 3 , consisting of acid dissolution, solvent extraction, and pH control processes, followed by a high-purity sulfation process. All of the produced ultra-high-purity Gd 2 (SO 4 ) 3 • 8H 2 O is assayed by inductively coupled plasma mass spectrometry and high-purity germanium detectors to evaluate its quality. Because of the long measurement time of high-purity germanium detectors, we have employed several underground laboratories for making parallel measurements including the Laboratorio Subterráneo de Canfranc in Spain, Boulby in the UK, and Kamioka in Japan. In the first half of production, the measured batch purities were found to be consistent with the specifications. However, in the latter half, the Gd 2 (SO 4 ) 3 • 8H 2 O contained one order of magnitude more 228Ra than the budgeted mean contamination. This was correlated with the corresponding characteristics of the raw material Gd 2 O 3 , in which an intrinsically large contamination was present. Based on their modest impact on SK physics, they were nevertheless introduced into the detector. To reduce 228 Ra for the next stage of gadolinium loading to SK, a new process has been successfully established.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Development of Low-cost Magnetocaloric Materials - CRADA 446

The overall goal of the project is to develop a faster heat-treatment process to produce low-cost high-performance magnetocaloric materials (MCM) for magnetic refrigeration technology. This research is in support of DOE-Fuel Cell Technology Office’s efforts to develop energy-efficient magnetic refrigeration technology for hydrogen liquefaction. Magnetic refrigeration offers a lower-cost and more energy-efficient alternative to traditional compression-based refrigeration technologies for liquefaction of gaseous hydrogen. Thus, PNNL is working with its industrial partner who is engaged in discovery, development and commercialization of low-cost high-performance MCM for use in magnetic refrigeration systems. Currently used MCM are typically a mixture of rare-earth and other elements. These are made in small batches and often need to be annealed for long durations, ranging from days to weeks, to obtain a good performance. Such extremely long heat-treatments add to the overall cost and increase the lead time to market of the commercial product. Therefore, this project will use recently developed innovative heat-treatment techniques at PNNL to shorten the annealing times and enhance the performance and lower the processing cost of MCM.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Compositional Variation Tests on DuraMelter 100 with LAW Sub-Envelope C1 Feed (LAWC22) Glass in Support of the LAW Pilot Melter (Final Report)

The Vitreous State Laboratory at The Catholic University of America (VSL) is developing and testing glass formulations for RPP-WTP waste envelopes to provide data to meet the RPP-WTP contract requirements and to support system design activities. That work is based upon small-scale batch melts (“crucible melts”) using waste envelope simulants. Selected formulations have also been tested in small-scale continuously-fed joule-heated melters (DM10 and DM100 systems) and, ultimately, in the LAW Pilot Melter. Such melter tests provide information on key process factors such as feed processing behavior, dynamic effects during processing, sulfate incorporation, processing rates, off-gas amounts and compositions, foaming control, etc., that cannot be reliably obtained from crucible melts. This sequential scale-up approach in the vitrification testing program ensures that maximum benefit is obtained from the more costly pilot-scale tests and that the most effective use is made of that resource. The principal objective of the work described in this report was to collect the necessary small-scale melter test data with a LAW Sub-Envelope C1 waste simulant in order to support the next series of tests with the same melter feed on the LAW Pilot Melter. This work was conducted under a corresponding Test Specification and Test Plan.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Underwater microwave ignition of hydrophobic thermite powder enabled by the bubble-marble effect

Highly energetic thermite reactions could be useful for a variety of combustion and material-processing applications, but their usability is yet limited by their hard ignition conditions. Furthermore, in virtue of their zero-oxygen balance, exothermic thermite reactions may also occur underwater. However, this feature is also hard to utilize because of the hydrophobic properties of the thermite powder, and its tendency to agglomerate on the water surface rather than to sink into the water. The recently discovered bubble-marble (BM) effect enables the insertion and confinement of a thermite-powder batch into water by a magnetic field. Here, we present a phenomenon of underwater ignition of a thermite-BM by localized microwaves. The thermite combustion underwater is observed in-situ, and its microwave absorption and optical spectral emission are detected. The vapour pressure generated by the thermite reaction is measured and compared to theory. The combustion products are examined ex-situ by X-ray photo-electron spectroscopy which verifies the thermite reaction. Potential applications of this underwater combustion effect are considered, e.g., for detonation, wet welding, thermal drilling, material processing, thrust generation, and composite-material production, also for other oxygen-free environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Large-scale dissolution of sintered Mo disks

Non-uranium production of 99 Mo via neutron capture or by photonuclear reaction using an electron accelerator is receiving considerable attention. For commercial production of 99 Mo, post-irradiation processes must incorporate a robust design for easy scale-up. Once developed, large-scale chemical processes must be optimized for hot-cell operations and potential automation. In this work, we present experimental results on the large-scale dissolution of sintered Mo disks using three 50% hydrogen peroxides from different suppliers. Dissolution rates obtained for 600-g Mo batches and potential reasons for different dissolution behaviors is discussed.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Predicting Sintering Window of Binder Jet Additively Manufactured Parts Using a Coupled Data Analytics and CALPHAD Approach

Batch-to-batch variation in powder compositions for binder jet additive manufacturing (BJAM) can significantly deter defining an “ideal” sintering window for a given alloy. One way to overcome the problem is by running sintering experiments at various temperatures for each batch of the powder. However, such an approach increases the time required to achieve large-scale production of parts. The predictive capabilities of computational thermodynamic tools like CALPHAD can be leveraged to overcome the challenge, especially for binder jet additive manufacturing, since the process occurs under near-equilibrium conditions. However, calculating the sintering window using CALPHAD can be computationally expensive, considering many possible feedstock compositions within “specification”. Here, we generate high throughput CALPHAD data for nickel-based superalloys to develop machine learning models to predict the sintering window rapidly. The predictive capability of the models has been validated using published results on BJAM of Inconel 718 and 625. Further, validated models are lightweight and can be deployed in an industrial setting to get sintering window in an accelerated manner.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Effect of 316 stainless steel powder processing conditions on microstructure

One parameter that has both economic and performance effects in the manufacturing of steel parts is the powder feedstock used. 316 L steel powder can be produced through water atomization or gas atomization, where both the powder size and the atomization process determine the cost of powder feedstock. Gas atomized powder is spherical and has a lower oxygen content than water atomized powder, making it the preferred choice for performance, but comes at a higher financial cost. Here, in this study, various 316 L powder batches are characterized to understand physical properties and microstructural variations. Density and flowability were determined using gas pycnometry and Hall flow tests. Powder morphology and porosity were qualitatively analyzed via optical microscopy and scanning electron microscopy, Finally, transmission electron microscopy was used to determine changes in phases present. Spherical gas atomized powder of 30–100 μm contained Mn$-$Si rich oxides both on the surface and within the matrix. Meanwhile, irregular water atomized powder 30 μm in diameter contained silicon oxides without manganese. All powder particles contained a nickel rich cellular structure which was shown to support the formation of additional phases. While literature has observed general microstructural features across 316 L powder particles, transmission electron microscopy (TEM) in this study has identified variations in precipitation and cell structures. Information regarding morphology, flowability, density, and phase distributions can be applied to understand variations in part consolidation, which will in turn show which powder aspects are significant for production.

Chemical segregation↗
DOE OSTI2023

Sequential Recovery of Critical Metals from Leached Liquor of Processed Spent Lithium-Ion Batteries

The processing and extraction of critical metals from black mass is important to battery recycling. Separation and recovery of critical metals (Co, Ni, Li, and Mn) from other metal impurities must yield purified metal salts, while avoiding substantial losses of critical metals. Solvent extraction in batch experiments were conducted using mixed metal sulphates obtained from the leach liquor obtained from spent and shredded lithium-ion batteries. Selective extraction of Mn 2+ , Fe 3+ , Al 3+ and Cu 2+ from simulated and real leached mixed metals solution was carried out using di-2-ethylhexylphophoric acid (D2EPHA) and Cyanex-272 at varying pH. Further experiments with the preferred extractant (D2EPHA) were performed under different conditions: changing the concentration of extractant, organic to aqueous ratio, and varying the diluents. At optimum conditions (40% v/v D2EPHA in kerosene, pH 2.5, O:A = 1:1, 25 °C, and 20 min), 85% Mn 2+ , 98% Al 3+ , 100% Fe 3+ , and 43% Cu 2+ were extracted with losses of only trace amounts (<5.0%) of Co 2+ , Ni 2+ , and Li + . The order of extraction efficiency for the diluents was found to be kerosene > Exxal-10 >>> dichloromethane (CH 2 Cl 2 ) > toluene. Four stages of stripping of metals loaded on D2EPHA were performed as co-extracted metal impurities were selectively stripped, and a purified MnSO 4 solution was produced. Spent extractant was regenerated after Fe 3+ and Al 3+ were completely stripped using 1.0 M oxalic acid (C 2 H 2 O 4 ).

25 ENERGY STORAGE↗
DOE OSTI2017

Formulation and Validation of an Efficient Computational Model for a Dilute, Settling Suspension Undergoing Rotational Mixing

Designing processing equipment for the mixing of settling suspensions is a challenging problem. Achieving low-cost mixing is especially difficult for the application of slowly reacting suspended solids because the cost of impeller power consumption becomes quite high due to the long reaction times (batch mode) or due to large-volume reactors (continuous mode). Further, the usual scale-up metrics for mixing, e.g., constant tip speed and constant power per volume, do not apply well for mixing of suspensions. As an alternative, computational fluid dynamics (CFD) can be useful for analyzing mixing at multiple scales and determining appropriate mixer designs and operating parameters. We developed a mixture model to describe the hydrodynamics of a settling cellulose suspension. The suspension motion is represented as a single velocity field in a computationally efficient Eulerian framework. The solids are represented by a scalar volume-fraction field that undergoes transport due to particle diffusion, settling, fluid advection, and shear stress. A settling model and a viscosity model, both functions of volume fraction, were selected to fit experimental settling and viscosity data, respectively. Simulations were performed with the open-source Nek5000 CFD program, which is based on the high-order spectral-finite-element method. Simulations were performed for the cellulose suspension undergoing mixing in a laboratory-scale vane mixer. The settled-bed heights predicted by the simulations were in semi-quantitative agreement with experimental observations. Further, the simulation results were in quantitative agreement with experimentally obtained torque and mixing-rate data, including a characteristic torque bifurcation. In future work, we plan to couple this CFD model with a reaction-kinetics model for the enzymatic digestion of cellulose, allowing us to predict enzymatic digestion performance for various mixing intensities and novel reactor designs.

09 BIOMASS FUELS↗
DOE OSTI2019

The Effect of Membrane Structure Prepared from Carboxymethyl Cellulose and Cellulose Nanofibrils for Cationic Dye Removal

Water-stable and eco-friendly membranes were fabricated from carboxymethyl cellulose (CMC) acting as anionic adsorbent and cellulose nanofibrils (CNFs) as strengthening filler by solvent- and unidirectional freeze-casting processes, both supported with simultaneous citric acid (CA) mediated cross-linking. Spectroscopic, thermogravimetric and potentiometric titration techniques were applied to evaluate the efficacy of the cross-linking as well as to quantify the processing-dependant surface charge. In addition, the CMC/CNF assembling and membrane porosity were identified microscopically as the combinatorial effect of components ratio and the applied fabrication technique. Finally, the membrane’s cationic dyes adsorption capacity and kinetic were evaluated depending on the dyes ionization constants, solution pH, and the contact time using batch equilibrium experiment, and further evaluated for filtration performance at optimal pH. The resulting, freeze-casted membranes demonstrate anisotropic to isotropic and highly (> 90%) porous structures with gradient pore sizes (from few nm up to 200 µm range). This provides relatively high and stable flux rates (150–190 kL/m{sup 2} h MPa) with ~ 100% cationic dye adsorption, fast dynamic (8.536–5.446 kg/g min) and capacity (1828–1398 g/kg), which highlight their potential in dead-end filtration technologies without need for additional separation step. The similar dye adsorption capacity was assessed for denser and nano-porous (< 50 nm) solvent-casted membranes, however, with much lower and time-declining flux rates (100–10 L/m{sup 2} h MPa), demonstrating their potential usage in spiral wound-cross-flow modules. Both types of membranes anyhow showed high dye removal capacity (≥ 90%) even after 4th (solvent-casted) and 50th (freeze-casted) reusing cycle, present a high-value alternative to commercial activated carbons or other bio-nano-absorbents.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

Advances in Online Monitoring for Measurement within Nuclear Fuel Reprocessing Streams

Abstract – Significant effort has been focused on the back end of the nuclear fuel cycle including treatment and reuse of irradiated fuel. Solvent extraction reprocessing methods that have been developed often contain various steps, with each one tailored to the separation of specific radionuclides, which are highly dependent upon solution properties. The instrumentation used to monitor these processes must be robust, require little or no maintenance, and be able to withstand harsh environments such as high radiation fields and aggressive chemical matrices. Our group has been investigating the use of optical spectroscopy for the on-line monitoring of actinides, lanthanides, and acid strength within fuel reprocessing streams. This paper describes the application of the electronic and vibrational spectroscopic techniques for radiochemical process monitoring. In this context, our team experimentally assessed the potential of Raman and UV-vis spectroscopic techniques for online real-time monitoring of the U(VI)/nitrate ion/nitric acid and Pu(VI/IV)/Np(VI/V/IV)/Nd(III) in solutions relevant to used nuclear fuel reprocessing. These techniques demonstrated robust performance in the repetitive batch measurements of each analyte in a wide concentration range using simulant and commercial dissolved used fuel solutions. Currently this has been demonstrated on the macroscopic scale, using sample probes requiring large solution volumes. In an effort to minimize waste and reduce dose to personnel, we have modified this technique to allow measurement at the microfluidic scale using a Raman microprobe. Under the current sampling environment, Raman samples typically require upwards of 10 mL and larger. Using the new sampling system, we can sample volumes at 10 µL or less, which is a scale reduction of over 1,000 fold in sample size. This will significantly reduce the requirements for handling hazardous materials, and greatly reduce the costs associated with worker protection from exposure to radioactive and hazardous materials, and costs due to waste disposal.

process monitoring, U, nitric acid, microfluidic, ↗
DOE OSTI2012

Fate and transport of phenol in a packed bed reactor containing simulated solid waste

Highlights: Black-Right-Pointing-Pointer Anaerobic column experiments were conducted at 37 Degree-Sign C using a simulated waste mixture. Black-Right-Pointing-Pointer Sorption and biodegradation model parameters were determined from batch tests. Black-Right-Pointing-Pointer HYDRUS simulated well the fate and transport of phenol in a fully saturated waste column. Black-Right-Pointing-Pointer The batch biodegradation rate and the rate obtained by inverse modeling differed by a factor of {approx}2. Black-Right-Pointing-Pointer Tracer tests showed the importance of hydrodynamic parameters to improve model estimates. - Abstract: An assessment of the risk to human health and the environment associated with the presence of organic contaminants (OCs) in landfills necessitates reliable predictive models. The overall objectives of this study were to (1) conduct column experiments to measure the fate and transport of an OC in a simulated solid waste mixture, (2) compare the results of column experiments to model predictions using HYDRUS-1D (version 4.13), a contaminant fate and transport model that can be parameterized to simulate the laboratory experimental system, and (3) determine model input parameters from independently conducted batch experiments. Experiments were conducted in which sorption only and sorption plus biodegradation influenced OC transport. HYDRUS-1D can reasonably simulate the fate and transport of phenol in an anaerobic and fully saturated waste column in which biodegradation and sorption are the prevailing fate processes. The agreement between model predictions and column data was imperfect (i.e., within a factor of two) for the sorption plus biodegradation test and the error almost certainly lies in the difficulty of measuring a biodegradation rate that is applicable to the column conditions. Nevertheless, a biodegradation rate estimate that is within a factor of two or even five may be adequate in the context of a landfill, given the extended retention time and the fact that leachate release will be controlled by the infiltration rate which can be minimized by engineering controls.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

ZeoNet: 3D convolutional neural networks for predicting adsorption in nanoporous zeolites

Zeolites are one of the most widely used materials in the chemical industry due to their nanometer-sized pores that can adsorb and react upon molecules selectively. With hundreds of known framework topologies and hundreds of thousands of computationally predicted structures, the ability to rapidly predict zeolite performance allows researchers to prioritize their efforts on the most promising structures for a given application. Although the accuracy of forcefield-based atomistic simulations has advanced significantly in the past two decades, these simulations can be computationally expensive, especially for long-chain, complex molecules. Here, we present ZeoNet, a representation learning framework using convolutional neural networks (ConvNets) and 3D volumetric representations for predicting adsorption in zeolites. ZeoNet was trained on the task of predicting Henry's constants for adsorption, k H , of n-octadecane in more than 330 000 known and predicted zeolite materials. Employing a 3D grid based on the distances to solvent-accessible surfaces, a volumetric representation that can be generated efficiently, the best-performing ZeoNet achieved a correlation coefficient r 2 = 0.977 and a mean-squared error MSE = 3.8 in ln k H , which corresponds to an error of 9.3 kJ mol -1 in adsorption free energy. In comparison, a model based on hand-designed geometric features has values of r 2 = 0.783 and MSE = 35.7. ZeoNet is also relatively efficient and can process ≈8 structures per second on an Nvidia RTX 2080TI GPU, orders of magnitude faster than forcefield-based simulations. A systematic analysis was conducted to investigate how the choice of ConvNet architectures, the linear dimension (L) and spatial resolution (Δd) of the distance grids, batch size, optimizer, and learning rate impact the model performance. We found that ConvNets based on the ResNet architecture offer the best tradeoff between expressiveness and efficiency. The performance for all models reaches a plateau at L = 30–45 Å and depends less sensitively on grid resolution, with a small benefit around Δd = 0.30–0.45 Å. Finally, saliency maps were visualized to identify which regions of the materials contributed the most to model predictions. It was found, interestingly, that the predictions are driven primarily by the accessible pore volume rather than the region occupied by the framework atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Online State Estimation for Time-Varying Systems

The paper investigates the problem of estimating the state of a time-varying system with a linear measurement model; in particular, the paper considers the case where the number of measurements available can be smaller than the number of states. In lieu of a batch linear least-squares (LS) approach well-suited for static networks, where a sufficient number of measurements could be collected to obtain a full-rank design matrix the paper proposes an online algorithm to estimate the possibly time-varying state by processing measurements as and when available. The design of the algorithm hinges on a generalized LS cost augmented with a proximal-point-type regularization. With the solution of the regularized LS problem available in closed-form, the online algorithm is written as a linear dynamical system where the state is updated based on the previous estimate and based on the new available measurements. Conditions under which the algorithmic steps are in fact a contractive mapping are shown, and bounds on the estimation error are derived for different noise models. Numerical simulations are provided to corroborate the analytical findings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Actual-Waste Testing of Ultraviolet Light to Augment the Enhanced Chemical Cleaning of SRS Sludge

In support of Savannah River Site (SRS) tank closure efforts, the Savannah River National Laboratory (SRNL) conducted Real Waste Testing (RWT) to evaluate Enhanced Chemical Cleaning (ECC), an alternative to the baseline 8 wt% oxalic acid (OA) chemical cleaning technology for tank sludge heel removal. ECC utilizes a more dilute OA solution (2 wt%) and an oxalate destruction technology using ozonolysis with or without the application of ultraviolet (UV) light. SRNL conducted tests of the ECC process using actual SRS waste material from Tanks 5F and 12H. The previous phase of testing involved testing of all phases of the ECC process (sludge dissolution, OA decomposition, product evaporation, and deposition tank storage) but did not involve the use of UV light in OA decomposition. The new phase of testing documented in this report focused on the use of UV light to assist OA decomposition, but involved only the OA decomposition and deposition tank portions of the process. Compared with the previous testing at analogous conditions without UV light, OA decomposition with the use of UV light generally reduced time required to reach the target of <100 mg/L oxalate. This effect was the most pronounced during the initial part of the decomposition batches, when pH was <4. For the later stages of each OA decomposition batch, the increase in OA decomposition rate with use of the UV light appeared to be minimal. Testing of the deposition tank storage of the ECC product resulted in analogous soluble concentrations regardless of the use or non-use of UV light in the ECC reactor.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗