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Multidisciplinary concurrent optimization framework for multi-phase building design process

Modern day building design projects require multidisciplinary expertise from architects and engineers across various phases of the design (conceptual, preliminary, and detailed) and construction processes. The Architecture Engineering and Construction (AEC) community has recently shifted gears toward leveraging design optimization techniques to make well-informed decisions in the design of buildings. However, most of the building design optimization efforts are either multidisciplinary optimization confined to just a specific design phase (conceptual/preliminary/detailed) or single disciplinary optimization (structural/thermal/daylighting/energy) spanning across multiple phases. Complexity in changing the optimization setup as the design progresses through subsequent phases, interoperability issues between modeling and physics-based analysis tools used at later stages, and the lack of an appropriate level of design detail to get meaningful results from these sophisticated analysis tools are few challenges that limit multi-phase multidisciplinary design optimization (MDO) in the AEC field. Here this paper proposes a computational building design platform leveraging concurrent engineering techniques such as interactive problem structuring, simulation-based optimization using meta models for energy and daylighting (machine learning based) and tradespace visualization. The proposed multi-phase concurrent MDO framework is demonstrated by using it to design and optimize a sample office building for energy and daylighting objectives across multiple phases. Furthermore, limitations of the proposed framework and future avenues of research are listed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Microscale Thermophoresis (MST) as a Tool to Study Binding Interactions of Oxygen-Sensitive Biohybrids

Microscale thermophoresis (MST) is a technique used to measure the strength of molecular interactions. MST is a thermophoretic-based technique that monitors the change in fluorescence associated with the movement of fluorescent-labeled molecules in response to a temperature gradient triggered by an IR LASER. MST has advantages over other approaches for examining molecular interactions, such as isothermal titration calorimetry, nuclear magnetic resonance, biolayer interferometry, and surface plasmon resonance, requiring a small sample size that does not need to be immobilized and a high-sensitivity fluorescence detection. In addition, since the approach involves the loading of samples into capillaries that can be easily sealed, it can be adapted to analyze oxygen-sensitive samples. In this Bio-protocol, we describe the troubleshooting and optimization we have done to enable the use of MST to examine protein–protein interactions, protein–ligand interactions, and protein–nanocrystal interactions. The salient elements in the developed procedures include 1) loading and sealing capabilities in an anaerobic chamber for analysis using a NanoTemper MST located on the benchtop in air, 2) identification of the optimal reducing agents compatible with data acquisition with effective protection against trace oxygen, and 3) the optimization of data acquisition and analysis procedures. The procedures lay the groundwork to define the determinants of molecular interactions in these technically demanding systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The MicroBooNE Search for Single Photon Events

This note describes and presents preliminary results for the MicroBooNE analysis being developed to search for neutrino-induced neutral current single photon events in the MicroBooNE detector. The analysis currently assumes neutrino neutral current Δ production followed by Δ radiative decay on argon (NC Δ → N γ) as the “signal model”; event reconstruction and selection have been developed and are being optimized in order to reduce cosmogenic and other beam-related backgrounds explicit to the NC Δ → N γ process. This note presents the current status of event reconstruction, selection, optimization and validation checks for the early stages of analysis on external (cosmogenic background) events. Also presented are the projected sensitivities for testing the standard model predicted rate for the NC Δ → N γ process and for testing the interpretation of the previously observed MiniBooNE low energy excess as NC Δ → N γ events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Integration and Optimization of a Waste Heat Driven Organic Rankine Cycle for Power Generation in Wastewater Treatment Plants

The study focuses on achieving energy self-sufficiency in Wastewater Treatment Plants by proposing a comprehensive model for integrating, sizing, and optimizing an Organic Rankine Cycle system. The Organic Rankine Cycle system is designed to utilize waste heat from the gensets at As Samra Wastewater Treatment Plant in Jordan, where it will contribute to the overall electrical energy supply of the plant. Real data from As Samra Wastewater Treatment Plant is used to model and calculate the available waste heat using TRNSYS® software. The Organic Rankine Cycle model is then developed using ASPEN PLUS® software to explore the impact of operational parameters and determine their optimal values for maximizing the plant's energy profile. An economic analysis is conducted to assess the feasibility of the proposed model, considering system components, installation, operation, and maintenance costs. To optimize the Organic Rankine Cycle system, the study employs the Multi-Output Support Vector Regression technique to capture nonlinear relationships between independent variables (fluid type, turbine inlet pressure, turbine inlet temperature, turbine outlet pressure, and mass flow rate) and dependent variables (pump power input, waste heat input, and turbine specific work). The Osprey optimization algorithm is used to address the multi-objective optimization problem, with the proposed Pareto-based Osprey Optimization Algorithm and the Multi-Objective Particle Swarm Optimization technique being employed to evaluate critical performance and economic parameters such as system thermal efficiency, net power output, and the levelized cost of electricity. The results of the optimization strategies indicate that the M-SVR model's prediction accuracy is significantly improved after parameter optimization, with the model returning high R 2 and low Mean Square Error values of 0.991 and 0.00216, respectively. The Pareto-Based Osprey Optimization Algorithm optimizer identifies the best working fluid as Isobutane/Isopentane in a ratio of 66:34, with optimal turbine inlet pressure and temperature of 15 bars and 218 °C, respectively. In conclusion, the Organic Rankine Cycle model at these optimal conditions achieves a cycle efficiency of 19.93% and an Levelized Cost of Electricity value of 0.0353 USD/kWh.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Materials and Methods for Streamlined Laboratory Analysis of Environmental Samples, FY 2016 Report

The International Atomic Energy Agency (IAEA) relies upon laboratory analysis of environmental samples (typically referred to as “swipes”) collected during on-site inspections of safeguarded facilities to support the detection and deterrence of undeclared activities. Unfortunately, chemical processing and assay of the samples is slow and expensive. A rapid, effective, and simple extraction process and analysis method is needed to provide certified results with improved timeliness at reduced costs (principally in the form of reduced labor), while maintaining or improving sensitivity and efficacy. To address these safeguard needs the Pacific Northwest National Laboratory (PNNL) explored and demonstrated improved methods for environmental sample (ES) analysis. Improvements for both bulk and particle analysis were explored. To facilitate continuity and adoption, the new sampling materials and processing methods will be compatible with existing IAEA protocols for ES analysis. PNNL collaborated with Oak Ridge National Laboratory (ORNL), which performed independent validation of the new bulk analysis methods and compared performance to traditional IAEA’s Network of Analytical Laboratories (NWAL) protocol. ORNL efforts are reported separately. This report describes PNNL’s FY 2016 progress, which was focused on analytical application supporting environmental monitoring of uranium enrichment plants and nuclear fuel processing. In the future the technology could be applied to other safeguard applications and analytes related to fuel manufacturing, reprocessing, etc. PNNL’s FY 2016 efforts were broken into two tasks and a summary of progress, accomplishments and highlights are provided below. Principal progress and accomplishments on Task 1, Optimize Materials and Methods for ICP-MS Environmental Sample Analysis, are listed below. • Completed initial procedure for rapid uranium extraction from ES swipes based upon carbonate-peroxide chemistry (delivered to ORNL for evaluation). • Explored improvements to carbonate-peroxide rapid uranium extraction chemistry. • Evaluated new sampling materials and methods (in collaboration with ORNL). • Demonstrated successful ES extractions from standard and novel swipes for a wide range uranium compounds of interest including UO 2 F 2 and UO 2 (NO 3 ) 2 , U 3 O 8 and uranium ore concentrate. • Completed initial discussions with commercial suppliers of PTFE swipe materials. • Submitted one manuscript for publication. Two additional drafts are being prepared. Principal progress and accomplishments on Task 2, Optimize Materials and Methods for Direct SIMS Environmental Sample Analysis, are listed below. • Designed a SIMS swipe sample holder that retrofits into existing equipment and provides simple, effective, and rapid mounting of ES samples for direct assay while enabling automation and laboratory integration. • Identified preferred conductive sampling materials with better performance characteristics. • Ran samples on the new PNNL NWAL equivalent Cameca 1280 SIMS system. • Obtained excellent agreement between isotopic ratios for certified materials and direct SIMS assay of very low levels of LEU and HEU UO 2 F 2 particles on carbon fiber sampling material. Sample activities range from 1 to 500 CPM (uranium mass on sample is dependent upon specific isotope ratio but is frequently in the subnanogram range). • Found that the presence of the UF molecular ions, as measured by SIMS, provides chemical information about the particle that is separate from the uranium isotopics and strongly suggests that those particles originated from an UF6 enrichment activity. • Submitted one manuscript for publication. Another manuscript is in preparation.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Selecting registration schemes in case of interstitial lung disease follow-up in CT

Purpose: Primary goal of this study is to select optimal registration schemes in the framework of interstitial lung disease (ILD) follow-up analysis in CT. Methods: A set of 128 multiresolution schemes composed of multiresolution nonrigid and combinations of rigid and nonrigid registration schemes are evaluated, utilizing ten artificially warped ILD follow-up volumes, originating from ten clinical volumetric CT scans of ILD affected patients, to select candidate optimal schemes. Specifically, all combinations of four transformation models (three rigid: rigid, similarity, affine and one nonrigid: third order B-spline), four cost functions (sum-of-square distances, normalized correlation coefficient, mutual information, and normalized mutual information), four gradient descent optimizers (standard, regular step, adaptive stochastic, and finite difference), and two types of pyramids (recursive and Gaussian-smoothing) were considered. The selection process involves two stages. The first stage involves identification of schemes with deformation field singularities, according to the determinant of the Jacobian matrix. In the second stage, evaluation methodology is based on distance between corresponding landmark points in both normal lung parenchyma (NLP) and ILD affected regions. Statistical analysis was performed in order to select near optimal registration schemes per evaluation metric. Performance of the candidate registration schemes was verified on a case sample of ten clinical follow-up CT scans to obtain the selected registration schemes. Results: By considering near optimal schemes common to all ranking lists, 16 out of 128 registration schemes were initially selected. These schemes obtained submillimeter registration accuracies in terms of average distance errors 0.18 ± 0.01 mm for NLP and 0.20 ± 0.01 mm for ILD, in case of artificially generated follow-up data. Registration accuracy in terms of average distance error in clinical follow-up data was in the range of 1.985–2.156 mm and 1.966–2.234 mm, for NLP and ILD affected regions, respectively, excluding schemes with statistically significant lower performance (Wilcoxon signed-ranks test, p < 0.05), resulting in 13 finally selected registration schemes. Conclusions: Selected registration schemes in case of ILD CT follow-up analysis indicate the significance of adaptive stochastic gradient descent optimizer, as well as the importance of combined rigid and nonrigid schemes providing high accuracy and time efficiency. The selected optimal deformable registration schemes are equivalent in terms of their accuracy and thus compatible in terms of their clinical outcome.

60 APPLIED LIFE SCIENCES↗

Groundwater Monitoring Optimization of Post Closure Waste Sites at SRS - 13184

Groundwater monitoring at the Savannah River Site (SRS) is required at dozens of waste sites and includes sampling at over 1,000 monitoring wells. The expected longevity of groundwater contamination and associated groundwater monitoring and reporting constitutes a significant long-term cost that represents an increasing proportion of the environmental management budget as surface waste units are closed. Therefore, a comprehensive evaluation of the monitoring program for eighteen regulated waste units was conducted to identify areas where monitoring could be optimized. The units evaluated varied considerably in the scope of monitoring; ranging from two wells to hundreds of wells. In order to systematically evaluate such disparate monitoring networks, SRS developed a decision-logic analysis using flow sheets to address potential areas of optimization. Five areas were identified for evaluation, including: (1) Comparison of current monitoring to regulatory requirements, (2) Spatial distribution, (3) Temporal sampling, (4) Analyte requirements, and (5) Reporting frequency and content. Optimization recommendations were made for fifteen of the eighteen groundwater units. The spatial evaluation resulted in recommendations to suspend sampling in 79 wells and add sampling at 16 wells. The temporal evaluation resulted in recommendations to reduce the number of well visits per year by 504. Analyte reductions were recommended at three groundwater units, with increases at three other units. Reporting frequency reductions were recommended for five units. Approximately $700,000 (direct dollars) of potential annualized cost savings were identified for these groundwater units, provided all recommendations are approved. The largest area of savings was associated with reducing the reporting frequency. The optimization approach has been presented to the EPA and South Carolina Department of Environmental Control (SCHDEC), with unit-specific recommendations approved for all five units presented. This approach can be expected to be highly successful for sites with rich historical data sets and where the requirements in regulatory monitoring plans can be negotiated. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Synthetic Control of the Photoluminescence Stability of Organolead Halide Perovskites

An optimized synthetic procedure for preparing photostable nanocrystalline methylammonium lead halide materials is reported. The procedure was developed by adjusting the lead halide to methylammonium/octylammonium halide precursor ratio. At a high precursor ratio (1:3), a blue-shifted photoinduced luminescence peak is measured at 642 nm for CH 3 NH 3 PbI 3 with 0.01 to 12 mJ pulsed-laser irradiation. The appearance of this peak is reversible over 300 min upon blocking the irradiation. In order to determine if the peak is the result of a phase change, in situ x-ray diffraction measurements were performed. No phase change was measured with an irradiance that causes the appearance of the photoinduced luminescence peak. Luminescence microscpectroscopy measurements showed that the use of a lower precursor ratio (1:1.5) produces CH 3 NH 3 PbI 3 and CH 3 NH 3 PbBr 3 perovskites that are stable over 4 min of illumination. Given the lack of a measured phase change, and the dependence on the precursor ratio, the photoinduced luminesce peak may derive from surface trap states. Finally, the enhanced photostability of the resulting perovskite nanocrystals produced with the optimized synthetic procedure supports their use in stable optoelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sizing Energy Storage System for Energy Arbitrage in Extreme Fast Charging Station

This paper proposes a non-linear programming (NLP) model to optimally size the energy storage system (ESS) and obtain an optimal energy management for energy arbitrage of an extreme fast charging station (XFCS) for electric vehicles (EVs), with minimized total cost of XFCS operation and ESS investment. Different from most reported work on sizing the ESS for EV charging stations, this paper proposes a pragmatic approach to model the ESS life degradation and accurately count the ESS cycles. Moreover, this work incorporates the peak demand charges in the operational cost of the charging station which are often overlooked in the literature. The proposed model is formulated and solved using AIMMS. Finally, a thorough sensitivity analysis is performed to offer insights into how different input parameters impact the ESS sizing and savings from the energy arbitrage perspective.

25 ENERGY STORAGE↗

Prototype Modeling for a Light-Trapping Planar-Cavity Enclosed Particle Solar Receiver

Concentrating solar thermal (CST) systems present a promising avenue for affordable and reliable energy production. Solar receivers are key components that determine the efficiency and longevity of these systems. Particle-based solar receivers have emerged as a compelling alternative to traditional technologies, offering several advantages that address limitations in current CST systems. This is especially true as next-generation CST technologies target applications including electricity generation, thermochemical processes, and industrial process heat, many of which necessitate higher operating temperatures than current commercial molten salt systems. Molten-salt thermal energy storage (TES) systems, commonly used in CSP, face challenges related to freezing and corrosion. Particle-based TES systems, in contrast, do not experience these issues, as particles are stable at high temperatures, exceeding 1000 degrees Celsius. This capability allows for a wider range of applications, including those requiring higher temperatures for industrial processes and efficient electricity generation. A novel innovation in particle-based solar receiver technology is the light-trapping planar cavity receiver (LTPCR) configuration developed by NREL. The LTPCR design consists of small cavity-like structures using opaque planar surfaces, enabling efficient capture and absorption of solar energy. A high incident flux concentration at the cavity aperture is absorbed on the receiver walls, and subsequently transferred to particles on the inside of cavities. The particles flow through the system, forming a fluidized bed inside of the receiver panels, effectively capturing the absorbed solar heat. Air is used as a fluidizing medium in this process to enhance particle heat transfer and mixing. The effectiveness of this design lies in its ability to manage solar flux conditions and ensure high solar-to-thermal receiver efficiency. A 100-kW prototype is currently being tested at the King Saud University in Saudi Arabia to assess the receiver performance. A range of modeling analyses for the optical, thermal, and mechanical effects were conducted to assess the performance of the receiver under on-sun conditions. The solar flux resulting from the KSU heliostat field was modeled using NREL SolTrace software and produced up to 600 kW/m2 at the receiver aperture. The solar flux absorbed on the receiver walls was then used within a computational fluid dynamics (CFD) model to predict wall temperature distributions along with radiation and convection loss. A two-phase CFD model was developed for the fluidized bed of silica sand inside the receiver panels to predict local wall-to-particle heat transfer coefficients, particle temperature distributions, and outlet temperature of the particles. We have also conducted analyses to understand the thermomechanical behavior of these innovative enclosed light-trapping solar receivers optimized for particle heating. We used finite element analysis (FEA) to predict the receiver's performance using temperature distributions obtained from CFD and based on the resulting stress profiles, evaluated creep-fatigue damage with a goal of achieving a 30-year service life. Analysis showed a significant impact of the particle-to-wall heat transfer coefficients (HTCs) on receiver performance, with higher HTCs resulting in reduced stress and increased lifespan. For instance, when using Inconel 740H, increasing the HTC from 800 W/m2 K to 1400 W/m2 K increased the creep life from 4,000 hours to over 100,000 hours. This highlights the importance of understanding and optimizing heat transfer in the design of high-efficiency receivers.

14 SOLAR ENERGY↗

Design optimization of lightweight automotive seatback through additive manufacturing compression overmolding of metal polymer composites

With the growing demand for enhanced automotive fuel efficiency and environmental sustainability, there is a need for lightweighting automotive components through innovative design and manufacturing processes. Here, this study leverages a combination of numerical iterative design optimization and hybrid additive manufacturing–compression molding (AM-CM) technique for metal polymer composites to lightweight an automotive seatback. The AM-CM process enables robust mechanical interlocking between metals and composites, boasting high stiffness and strength with low overall density. Replacing metallic components with such metal polymer composites allows for comparable mechanical performance while significantly reducing the overall weight. First, the automotive seatback design space is reduced to critical load carrying regions using topology optimization and high stress concentration areas are identified using finite element analysis. Next, a lightweight metal polymer subcomponent is designed for a high stress concentration region. The full seatback frame with spatially heterogeneous material-specific design is then iteratively optimized to enable enhanced stiffness with minimal weight. Overall, the automotive seatback frame designed with location-specific metal, polymer, and metal polymer composite materials weighs 20% less than the metal-only design while exhibiting similar stiffness.

36 MATERIALS SCIENCE↗

Designing and optimizing highly efficient grating for high-brightness laser based on spectral beam combining

A highly efficient nano-periodical grating is theoretically investigated for spectral beam combining (SBC) and is experimentally implemented for attaining high-brightness laser from a diode laser array. The rigorous coupled-wave analysis with the S matrix method is employed to optimize the parameters of the grating. According the optimized parameters, the grating is fabricated and plays a key role in SBC cavity. The diffraction efficiency of this grating is optimized to 95% for the output laser which is emitted from the diode laser array. The beam parameter product of 3.8 mm mrad of the diode laser array after SBC is achieved at the output power of 46.3 W. The optical-to-optical efficiency of SBC cavity is measured to be 93.5% at the maximum operating current in the experiment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Digestion processes and elemental analysis of oxide and sulfide solid electrolytes

Detailed elemental analysis is essential for a successful development and optimization of material systems and synthesis methods. This is especially relevant for Li- and Na-containing compounds, found in state-of-the-art and next-generation battery systems. Their materials’ properties and thus the final device performance strongly depend on the crystal structure, the stoichiometry, and defect chemistry, e.g., influencing charge carrier concentration and activation energies for vacancy transport. However, a detailed quantitative analysis of light elements in a heavy matrix, featuring a broad range of solubilities and vapor pressures, is often difficult and associated with large uncertainties and thus neglected in favor of just reporting the stoichiometry as “weighed in.” Here, in this work, we report several approaches to digest and dissolve various oxide and sulfide-based materials, used in next-generation Li batteries, for elemental analysis via optical emission spectroscopy. These include the most common solid electrolytes Li-La-Ti–O, a perovskite material (LLTO), and Li-La-Zr-O which has garnet structure (LLZO). Additionally, a facile thermal digestion process is reported for a surrogate sulfide solid electrolyte (Na 2 S). The digestion procedures reported here are suitable for almost any laboratory environment and, when applied, will improve understanding of the synthesis-structure–property correlations needed to advanced batteries with all solid-state configurations.

Malkowski, Thomas F.↗

Sparse Overcomplete Denoising: Aggregation Versus Global Optimization

Denoising is often addressed via sparse coding with respect to an overcomplete dictionary. There are two main approaches when the dictionary is composed of translates of an orthonormal basis. The first, traditionally employed by techniques such as wavelet cycle spinning, separately seeks sparsity w.r.t. each translate of the orthonormal basis, solving multiple partial optimizations and obtaining a collection of sparse approximations of the noise-free image, which are aggregated together to obtain a final estimate. The second approach, recently employed by convolutional sparse representations, instead seeks sparsity over the entire dictionary via a global optimization. It is tempting to view the former approach as providing a suboptimal solution of the latter. In this letter, we analyze whether global sparsity is a desirable property, and under what conditions the global optimization provides a better solution to the denoising problem. In particular, our experimental analysis shows that the two approaches attain comparable performance in case of natural images and global optimization outperforms the simpler aggregation of partial estimates only when the image admits an extremely sparse representation. Here, we explain this phenomenon by separately studying the bias and variance of these solutions, and by noting that the variance of the global solution increases very rapidly as the original signal becomes less and less sparse.

97 MATHEMATICS AND COMPUTING↗

Thermal Analysis for SRS Saltstone Disposal Unit Facility

Saltstone Disposal Units (SDU) are long term disposal units for low activity grout produced from the solidification of decontaminated non-hazardous salt waste at SRS. The unit is a cylindrical disposal vault of 150 ft. in diameter and 23 ft. in height. The total volume the SDU can hold is 3 million gallons of grout. The hydration process of the grout material produces heat from an exothermic chemical reaction. If the grout reaches temperatures higher than the maximum safety temperature of 95 deg. C, cracks can start forming leading to contamination of the environment. The purpose of this study is to develop the optimal baseline domain boundary conditions and to perform a sensitivity analysis with respect to the baseline modeling conditions. The following assumptions were made for the modeling calculations: - The system geometry is axisymmetric; - The system was at steady state; - Ambient temperature was set to 100 deg. F; - Air was assumed to be an incompressible ideal gas; - Radiation was neglected for a conservative estimation; - Natural convection for the SDU vapor space is assumed to be turbulent because Rayleigh number based on typical operating conditions is higher than 10{sup 8}; - Water tables were not taken into consideration. The following sensitivity analyses were performed to find the optimal domain boundary: - Mesh size sensitivity; - Soil depth sensitivity - Soil depth varied from 30 ft to 250 ft with a soil thickness of 90 ft; - Soil thickness sensitivity - Soil thickness varied from 30 ft to 270 ft with a soil depth of 180 ft; - Soil conductivity sensitivity - Soil thermal conductivity varied from 0.25 W/m-K to 1 W/m-K; - Ambient Temperature Sensitivity - Ambient temperature varied from 70 deg. F to 110 deg. F. For the thermal calculations, the temperature of the bottom of the soil was set to 17.4 deg. C. The heat flux on the roof of the building and surface of the earth is 163.2 W/m{sup 2}. The soil sides are set to be adiabatic. The sensitivity analysis shows that the mesh size has no effect on the numerical results. This is mainly due to a small convection zone and large conduction zones in the modeling domain. The optimal domain boundary was found to be a soil thickness of 90 ft and a soil depth of 150 ft. The different sensitivity analysis performed here shows the optimal boundary domain to be used for thermal calculations is a soil depth of 150 ft beneath the SDU and a soil thickness of 90 ft. Anything larger would produce similar solutions but at a longer computational time to solve. The maximum temperature was more sensitive to soil properties as shown here. While the ambient temperature affected the max temperature linearly. Most of the heat transfer takes place downward vertically between the SDU and the soil beneath it. Using the optimal domain boundary determined by the sensitivity analyses, the maximum thermal loading to keep the maximum grout temperature below 95 deg. C is 1.646 W/m{sup 3}.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Bifurcation, chaos, and scan instability in dynamic atomic force microscopy

The dynamical motion at any point on the cantilever of an atomic force microscope can be expressed quite generally as a superposition of simple harmonic oscillators corresponding to the vibrational modes allowed by the cantilever shape. Central to the dynamical equations is the representation of the cantilever-sample interaction force as a polynomial expansion with coefficients that account for the interaction force “stiffness,” the cantilever-to-sample energy transfer, and the displacement amplitude of cantilever oscillation. Renormalization of the cantilever beam model shows that for a given cantilever drive frequency cantilever dynamics can be accurately represented by a single nonlinear mass-spring model with frequency-dependent stiffness and damping coefficients [S. A. Cantrell and J. H. Cantrell, J. Appl. Phys. 110, 094314 (2011)]. Application of the Melnikov method to the renormalized dynamical equation is shown to predict a cascade of period doubling bifurcations with increasing cantilever drive force that terminates in chaos. The threshold value of the drive force necessary to initiate bifurcation is shown to depend strongly on the cantilever setpoint and drive frequency, effective damping coefficient, nonlinearity of the cantilever-sample interaction force, and the displacement amplitude of cantilever oscillation. The model predicts the experimentally observed interruptions of the bifurcation cascade for cantilevers of sufficiently large stiffness. Operational factors leading to the loss of image quality in dynamic atomic force microscopy are addressed, and guidelines for optimizing scan stability are proposed using a quantitative analysis based on system dynamical parameters and choice of feedback loop parameter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A paradigm shift: an introduction to structured decision making for sustainable waste management and remediation - 15649

transport of contaminants and human health risk assessment. Most often these modeling activities are carried out in a conservative fashion, usually beyond even the conservatism that is built into the associated regulations and guidance. Decisions are aimed primarily at compliance with regulatory objectives, rather than optimization. This leads to unnecessarily costly remediation and under-utilization of the nation's relatively few radioactive waste disposal facilities. Risk assessment decisions under CERCLA and RCRA might seem to perform better, but if anything this is because the focus is on shorter-term decision-making because long term fate and transport modeling is not considered necessary in most cases. However, some more complex contamination problems suffer from the same basic issues as radioactive waste disposal in terms of the need for complex fate and transport modeling and subsequent risk assessment. At least CERCLA addresses optimization in the feasibility study, but it does not address how to perform that optimization in the face of uncertainty or stakeholders who have different competing objectives. Other environmental issues that fall outside the realm of DOE Orders, NRC regulations, and regulations such as CERCLA and RCRA, have found a different path towards effective decision-making. This includes land reuse and watershed management decisions, for which there is a focus on sustainability and on stakeholder involvement throughout the decision making process. EPA is using 'structured decision analysis' to achieve the primary goal of maximizing societal welfare. These same tools and approaches can be brought into environmental and waste management decisions that need to be made by DOE. Structured decision analysis provides a formal process for capturing not only the science side of the problem, but also the costs and value judgments of the stakeholders, to reach an optimal solution. But this approach requires a paradigm shift within the DOE and NRC environmental and waste management programs. That is, it requires a willingness to engage a new approach that will provide a path towards effective optimization in the decision-making process for the complex environmental problems faced by DOE and NRC. Because of the current nature of problem solving for these types of problems, which involves many layers of conservatism, this structured decision analysis path towards optimization will also realize substantial cost savings for these programs, while maintaining or improving defensibility and transparency in the decision making process. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Analysis of Conduction Cooling Strategies for Wire Arc Additive Manufacturing

Metal additive manufacturing (AM) processing consists of numerous parameters which take time to optimize for various geometries. One aspect of the metal AM process that continues to be explored is the control of thermal energy accumulation during component manufacturing due to the melting and solidification of the feedstock. Excessive energy accumulation causes thermal failure of the component while minimal energy accumulation causes lack of fusion with the build plate or previous layer. The ability to simulate the thermal response of an AM component can increase research efficiency by reducing the time to optimize thermal energy accumulation. This paper presents an effective implementation of finite element analysis to determine the thermal response of a wire arc additive manufactured component with various build plate sizes and cooling methods including, integral build plate cooling, oversized build plates with passive cooling, and non-integral build plate cooling. The use of integral build plate cooling channels was shown to decrease the interpass temperature at the conclusion of the build process by 55% and build plate temperature by 96% compared to the conventionally deposited sample with 20 second dwell time. The use of a tall build plate with passive cooling was shown to reduce the interpass temperature by 32% as compared to the conventionally deposited sample with 20 second dwell time. Each cooling strategy evaluated decreased the interpass temperature within a range of 20–55% which enables higher deposition rates and decreased dwell times during depositions. The cooling strategies are designed to be implemented in a hybrid or retrofit AM platform to mitigate concerns of the thermal input from the additive process having detrimental effects on the precision of the machining process. This paper shows that accurate simulations of all strategies can be used to accurately predict the thermal response of the various strategies discussed. These cooling strategies will allow for increased deposition rates with comparable interpass temperature and decreased dwell time, increasing deposition efficiency. This model and these simulations are verified by experimental results. It is concluded that passive strategies, such as the over-sized tall build plate, can be used when liquid coolant in the AM environment could negatively affect the deposition process. Active cooling strategies, such as the integral build plate cooling could be used if low thermal conductivity materials are deposited or higher material deposition rates are desired. This paper discusses the use of active and passive cooling used during AM and shows how a simulation model can be used to make design choices for cooling strategies. The model also enables verification of select critical process parameters such as dwell times for a desired interpass temperature.

Heinrich, Lauren↗