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The underlying mathematical formulation and issues associated with integrated control, structure, and optical design are discussed. Topics addressed include the development of cost functionals, optimization in the vector objective setting, and computational aspects of the optimization problem with special emphasis on model reduction strategies. Results on simple design problems are presented.
Large-eddy simulation (LES) has matured to the point where application to complex flows is desirable. The extension to higher Reynolds numbers leads to an impractical number of grid points with existing structured-grid methods. Furthermore, most real world flows are rather difficult to represent geometrically with structured grids. Unstructured-grid methods offer a release from both of these constraints. However, just as it took many years for structured-grid methods to be well understood and reliable tools for LES, unstructured-grid methods must be carefully studied before we can expect them to attain their full potential. In the past two years, important building blocks have been put into place making possible a careful study of LES on unstructured grids. The first building block was an efficient mesh generator which allowed the placement of points according to smooth variation of physical length scales. This variation of length scales is in all three directions independently, which allows a large reduction in points when compared to structured-grid methods, which can only vary length scales in one direction at a time. The second building block was the development of a dynamic model appropriate for unstructured grids. The principle obstacle was the development of an unstructured-grid filtering operator. In the past year, some of the new filters developed by Jansen have been implemented into a highly parallelized finite element code based on the Galerkin/least-squares finite element method. We have chosen the NACA 4412 airfoil at maximum lift as the first simulation for a variety of reasons. First, it is a problem of significant interest since it would be the first LES of an aircraft component. Second, this flow has been the subject of three experimental studies. The third reason for considering this flow is the variety of flow features which provide an important test of the dynamic model. Only the dynamic model can be expected to perform satisfactorily in this variety of situations: from the laminar regions where it must not modify the flow at all to the turbulent boundary layers and wake where it must represent a wide variety of subgrid-scale structures. The flow configuration we have chosen is that of Wadcock (1987) at Reynolds number based on chord Re(sub c) = u(sub infinity)c/v = 1.64 x 10(exp 6), Mach number M = 0.2, and 12 deg angle of attack.
The proton exchange membrane fuel cell (PEMFC) is one of the most promising electrochemical power sources for space and electric vehicle applications. The wide spectrum of R&D activities on PEMFC's, carried out in our Center from 1988 to date, is as follows (1) Electrode Kinetic and Electrocatalysis of Oxygen Reduction; (2) Optimization of Structures of Electrodes and of Membrane and Electrode Assemblies; (3) Selection and Evaluation of Advanced Proton Conducting Membranes and of Operating Conditions to Attain High Energy Efficiency; (4) Modeling Analysis of Fuel Cell Performance and of Thermal and Water Management; and (5) Engineering Design and Development of Multicell Stacks. The accomplishments on these tasks may be summarized as follows: (1) A microelectrode technique was developed to determine the electrode kinetic parameters for the fuel cell reactions and mass transport parameters for the H2 and O2 reactants in the proton conducting membrane. (2) High energy efficiencies and high power densities were demonstrated in PEMFCs with low platinum loading electrodes (0.4 mg/cm(exp 2) or less), advanced membranes and optimized structures of membrane and electrode assemblies, as well as operating conditions. (3) The modeling analyses revealed methods to minimize mass transport limitations, particularly with air as the cathodic reactant; and for efficient thermal and water management. (4) Work is in progress to develop multi-kilowatt stacks with the electrodes containing low platinum loadings.
The Quiet Spike F-15B flight research program investigated supersonic shock reduction using a 24-ft sub-scale telescoping nose boom on an F-15B airplane. The program primary flight test objective was to collect flight data for aerodynamic and structural models validation up to 1.8 Mach. Other objectives were to validate the mechanical feasibility of a morphing fuselage at the operational conditions and determine the near-field shock wave characterization. The stability and controls objectives were to assess the effect of the spike on the stability, controllability, and handling qualities of the aircraft and to ensure adequate stability margins across the entire research flight envelop. The two main stability and controls issues were the effects of the telescoping nose boom influenced aerodynamics on the F-15B aircraft flight dynamics and air data and angle of attack sensors. This paper reports on the stability and controls flight envelope clearance methods and flight test analysis of the F-15B Quiet Spike. Brief pilot commentary on typical piloting tasks, approach and landing, refueling task, and air data sensitivity to the flight control system are also discussed in this report.
The development of Vertical Take-off and Landing (VTOL) vehicles for the Urban Air Mobility (UAM) markets presents a need for light weight vehicle structures with effective occupant protection capabilities. The National Aeronautics and Space Administration (NASA) has been working to fill that need, recently developing a cadre of concept vehicles to help characterize UAM design feasibility. This paper describes a study, using these concept vehicles, to evaluate the use of advanced composite structure and energy attenuating designs in the UAM vehicle design space. A finite element model (FEM) of a single passenger quadrotor concept vehicle was developed in LS-Dyna® and simulated under nominal and off-nominal vertical impact conditions. A variety of energy attenuating design mechanisms were implemented within this model to quantify their effectiveness in improving occupant safety. The use of carbon composites in both the energy attenuation mechanisms and vehicle structure was evaluated. The results of this study found significant reduction in occupant injury risk with the implementation of energy absorbing composite crush tubes and landing gear within the vehicle design. Additionally the use of a carbon fiber as a structural material was found to provide significant weight reduction while maintaining similar occupant loads to that predicted with an aluminum structure. This work provides a preliminary evaluation of design mechanisms and materials that may be used to optimize occupant protection capabilities within the UAM market.
Here, this work summarizes a feasibility study on testing numerical algorithms that are suitable and efficient for advanced system analysis code development under the mutli-physics framework, MOOSE. The key to the test bed is the implementation of high-order one-dimensional staggered-grid finite volume method (SG-FVM), and its direct interaction with the linear/nonlinear solver, PETSc. The test bed utilized a more flexible code structure to enable the finite volume method implementation and direct interacting with the solver package, instead of using the natively supported finite element method by the framework. Using a suite of selected test problems with different problem sizes and levels of complexity, the implemented SG-FVM demonstrated superior performance improvement against a direct finite element method implementation through MOOSE. On two computer systems, the speedup was observed to be significant, with at least one order of magnitude of solving time reduction. For a complex reactor model, transient simulation was performed using the newly developed finite volume method code, the results of which agree very well with the reference results from the finite element method code. Overall, this study demonstrates a successful feasibility study on the proposed numerical algorithms and software structure to support advanced system analysis tool development.
Redox flow batteries are attractive technologies for grid energy storage since they use solutions of redox-active molecules that enable a superior scalability and the decoupling of power and energy density. However, the reaction mechanisms of the redox active components at RFB electrodes are complex, and there is currently a pressing need to understand how interfacial processes impact the kinetics and operational reversibility of RFB systems. Here, we developed a combined electrochemical imaging methodology rooted in scanning electrochemical microscopy (SECM) and atomic force microscopy (AFM) for exploring the impact of electrode structure and conditioning on the electron transfer properties of model redox-active dialkoxybenzene derivatives, 2,5-di-tert-butyl-1,4-bis(2-methoxyethoxy)benzene (C1) and 2,3-dimethyl-1,4-dialkoxybenzene (C7). Using AFM and secondary-ion mass spectrometry (SIMS), we observed the formation of interfacial films with distinct mechanical properties compared to those of cleaved graphitic surfaces, and exclusively during reduction of electrogenerated radical cations. These films had an impact on the median rate and distribution of the electron transfer rate constant at the basal plane of multilayer and single layer graphene electrodes, displaying kinetically-limited values that did not yield the activation expected per the Butler–Volmer model with a transfer coefficient ~0.5. These changes were dependent on redoxmer structure: furthermore, SECM showed strong attenuation of C7 kinetics by a surface layer on MLG and SLG, while C1 kinetics were only affected by SLG. SECM and AFM results together show that these limiting films operate exclusively on the basal plane of graphite, with the edge plane showing a relative insensitivity to cycling and operation potential. Ultimately, this integrated electrochemical imaging methodology creates new opportunities to understand the unique role of interfacial processes on the heterogeneous reactivity of redoxmers at electrodes for RFBs, with a future role in elucidating phenomena at high active concentrations and spatiotemporal variations in electrode dynamics.
Adults with type 2 diabetes (T2D) have a higher fracture risk for a given bone quantity, but the mechanisms remain unclear. Using a rat model of polygenic obese T2D, we demonstrate that diabetes significantly reduces whole-bone strength for a given bone mass (μCT-derived BMC), and we quantify the roles of T2D-induced deficits in material properties versus bone structure; ie, geometry and microarchitecture. Lumbar vertebrae and ulnae were harvested from 6-month-old lean Sprague-Dawley rats, obese Sprague-Dawley rats, and diabetic obese UCD-T2DM rats (diabetic for 69 ± 7 days; blood glucose >200 mg/dL). Both obese rats and those with diabetes had reduced whole-bone strength for a given BMC. In obese rats, this was attributable to structural deficits, whereas in UCD-T2DM rats, this was attributable to structural deficits and to deficits in tissue material properties. For the vertebra, deficits in bone structure included thinner and more rod-like trabeculae; for the ulnae, these deficits included inefficient distribution of bone mass to resist bending. Deficits in ulnar material properties in UCD-T2DM rats were associated with increased non-enzymatic crosslinking and impaired collagen fibril deformation. Specifically, small-angle X-ray scattering revealed that diabetes reduced collagen fibril ultimate strain by 40%, and those changes coincided with significant reductions in the elastic, yield, and ultimate tensile properties of the bone tissue. Importantly, the biomechanical effects of these material property deficits were substantial. Prescribing diabetes-specific tissue yield strains in high-resolution finite element models reduced whole-bone strength by a similar amount (and in some cases a 3.4-fold greater amount) as the structural deficits. These findings provide insight into factors that increase bone fragility for a given bone mass in T2D; not only does diabetes associate with less biomechanically efficient bone structure, but diabetes also reduces tissue ductility by limiting collagen fibril deformation, and in doing so, reduces the maximum load capacity of the bone.
This paper introduces a surrogate modeling scheme based on Grassmannian manifold learning to be used for cost-efficient predictions of high-dimensional stochastic systems. The method exploits subspace-structured features of each solution by projecting it onto a Grassmann manifold. This point-wise linear dimensionality reduction harnesses the structural information to assess the similarity between solutions at different points in the input parameter space. The method utilizes a solution clustering approach in order to identify regions of the parameter space over which solutions are sufficiently similarly such that they can be interpolated on the Grassmannian. In this clustering, the reduced-order solutions are partitioned into disjoint clusters on the Grassmann manifold using the eigen-structure of properly defined Grassmannian kernels and, the Karcher mean of each cluster is estimated. Then, the points in each cluster are projected onto the tangent space with origin at the corresponding Karcher mean using the exponential mapping. For each cluster, a Gaussian process regression model is trained that maps the input parameters of the system to the reduced solution points of the corresponding cluster projected onto the tangent space. Using this Gaussian process model, the full-field solution can be efficiently predicted at any new point in the parameter space. In certain cases, the solution clusters will span disjoint regions of the parameter space. In such cases, for each of the solution clusters we utilize a second, density-based spatial clustering to group their corresponding input parameter points in the Euclidean space. The proposed method is applied to two numerical examples. Here, the first is a nonlinear stochastic ordinary differential equation with uncertain initial conditions where the surrogate is used to predict the time history solution. The second involves modeling of plastic deformation in a model amorphous solid using the Shear Transformation Zone theory of plasticity, where the proposed surrogate is used to predict the full strain field of a material specimen under large shear strains.
Like no other sulfur host material, polyacrylonitrile-derived sulfurized carbon (SPAN) promises improved electrochemical performance for lithium–sulfur batteries, based on its compatibility with carbonate solvents and ability to prevent self-discharge and shuttle effect. However, a complete understanding of the SPAN’s lithiation mechanism is still missing because its structural features vary widely with synthesis conditions, and its electrochemical performance deviates from elemental sulfur. This study continues our research on the elucidation of the SPAN’s structural characteristics and lithiation mechanisms via computational approaches. Here, our models reproduce most experimental data regarding carbon’s graphitization level and conjugated ordering, sulfur–carbon covalent bonding, sulfur loading, and elemental composition. Our simulations emulate the discharge voltage observed in experiments for the first discharge, which reveals that sulfur follows multiple reduction pathways based on its interaction with the carbon backbone. Sulfur reduction takes place above 1.0 V vs Li/Li + mostly in the SPAN-like material, with no long-chain lithium polysulfide formation. Below 1.0 V vs Li/Li + , the backbone’s electrochemical activity occurs via multiple C–Li and N–Li interactions, mostly with edge carbon atoms and pyridinic nitrogen. Moreover, we identify Li + binding sites throughout the graphitized backbone that might lead to prohibited energy costs for Li + deintercalation, which may explain the irreversible capacity loss between the first and second discharges. This work improves understanding of lithiation mechanisms in sulfurized carbon, which is useful for rationally designing SPAN synthesis pathways tailored to increase sulfur loading and enhanced electrochemical performance.
Reduction of the earth's ozone layer, with a resultant increase in transmission of solar ultraviolet radiation in the 290 to 320nm waveband (UV-B), via space shuttle operations through the stratosphere is considered. It is shown that simulated solar ultraviolet radiation can, under experimental conditions, detrimentally affect the marine organisms that form the base of the food web of oceanic and estuarine ecosystems. Whether a small increase in biologically harmful ultraviolet radiation might overwhelm these mechanisms and produce changes that will have damaging consequences to the biosphere is discussed. The potential for irreversible damage to the productivity, structure and/or functioning of a model estuarine ecosystem by increased UV-B radiation and whether these ecosystems are highly stable or amenable to adaptive change is studied. Data are provided to assess the potential impact upon marine ecosystems if space shuttle operations contribute to a reduction of the stratospheric ozone layer and the sensitivity of key community components to increased UV-B radiation is examined.
Purpose: For image guidance tasks full image quality is not required throughout the entire image. With dynamic filtration of the kV imaging beam the noise properties of the CT image can be locally controlled, providing a high quality image around the target volume with a lower quality surrounding region while providing substantial dose sparing to the patient as well as reduced scatter fluence on the detector. Methods: A dynamic collimation device with 3mm copper blades has been designed to mount in place of the bowtie filter on the On-Board Imager (Varian Medical Systems). The beam intensity is reduced by 95% behind the copper filters and the aperture is controlled dynamically to conformally illuminate a given ROI during a standard cone-beam CT scan. A data correction framework to account for the physical effects of the collimator prior to reconstruction was developed. Furthermore, to determine the dose savings and scatter reduction a monte carlo model was built in BEAMnrc with specifics from the Varian Monte Carlo Data Package. The MC model was validated with Gafchromic film. Results: The reconstructed image shows image quality comparable to a standard scan in the specified ROI, with higher noise and streaks in the outer region but still sufficient information for alignment to high contrast structures. The monte carlo modeling showed that the scatter-to-primary ratio was reduced from 1.26 for an unfiltered scan to 0.45 for an intensity weighted scan, suggesting that image quality may be improved in the inner ROI. Dose in the inner region was reduced 10–15% due to reduced scatter and by as much as 75% in the outer region. Conclusion: Dynamic intensity-weighted ROI imaging allows reduction of imaging dose to sensitive organs away from the target region while providing images that retain their utility for patient setup and procedure guidance. Funding was provided in part by Varian Medical Systems and NIH Grants 1RO1CA120540, T32EB002103, S10 RR021039 and P30 CA14599. The contents of this work are solely the responsibility of the authors and do not necessarily represent the official views of any of the supporting organizations.
The high performance of polycrystalline CdTe thin film solar cells is enabled by annealing in the presence of Cl. This process is typically carried out for tens of minutes resulting in reduction of defect states within the bandgap among other beneficial effects. In this work, we investigate laser annealing as a means of rapidly annealing CdTe using a continuous wave sub-bandgap 1064 nm laser. The partial transmission of the beam allows us to monitor the annealing process in-situ and in real time. We find that optoelectronic and structural changes occur through two distinct kinetic processes resulting in the removal of deep defects and twinned regions, respectively. A multilayer optical model including surface roughness is used to interpret both the in-situ transmission as well as ex-situ reflectivity measurements. These experiments demonstrate beneficial material changes resulting from sub-bandgap laser-driven CdCl{sub 2} treatment of CdTe in minutes, which is an important step towards accelerating the processing of the CdTe absorber layer.
Puerto Rico faced a double strike from hurricanes Irma and Maria in 2017. The resulting damage required a comprehensive rebuild of electric infrastructure. There are plans and pilot projects to rebuild with microgrids to increase resilience. This paper provides a techno-economic analysis technique and case study of a potential future community in Puerto Rico that combines probabilistic microgrid design analysis with tiered circuits in building energy modeling. Tiered circuits in buildings allow electric load reduction via remote disconnection of non-critical circuits during an emergency. When coupled to a microgrid, tiered circuitry can reduce the chances of a microgrid's storage and generation resources being depleted. The analysis technique is applied to show 1) Approximate cost savings due to a tiered circuit structure and 2) Approximate cost savings gained by simultaneously considering resilience and sustainability constraints in the microgrid optimization. The analysis technique uses a resistive capacitive thermal model with load profiles for four tiers (tier 1-3 and non-critical loads). Three analyses were conducted using: 1) open-source software called Tiered Energy in Buildings and 2) the Microgrid Design Toolkit. For a fossil fuel based microgrid 30% of the total microgrid costs of 1.18 million USD were calculated where the non-tiered case keeps all loads 99.9% available and the tiered case keeps tier 1 at 99.9%, tier 2 at 95%, tier 3 at 80% availability, with no requirement on non-critical loads. The same comparison for a sustainable microgrid showed 8% cost savings on a 5.10 million USD microgrid due to tiered circuits. The results also showed 6-7% cost savings when our analysis technique optimizes sustainability and resilience simultaneously in comparison to doing microgrid resilience analysis and renewables net present value analysis independently. Though highly specific to our case study, similar assessments using our analysis technique can elucidate value of tiered circuits and simultaneous consideration of sustainability and resilience in other locations.
The prediction of space radiation induced cancer risk carries large uncertainties with two of the largest uncertainties being radiation quality and dose-rate effects. In risk models the ratio of the quality factor (QF) to the dose and dose-rate reduction effectiveness factor (DDREF) parameter is used to scale organ doses for cosmic ray proton and high charge and energy (HZE) particles to a hazard rate for γ-rays derived from human epidemiology data. In previous work, particle track structure concepts were used to formulate a space radiation QF function that is dependent on particle charge number Z, and kinetic energy per atomic mass unit, E. QF uncertainties where represented by subjective probability distribution functions (PDF) for the three QF parameters that described its maximum value and shape parameters for Z and E dependences. Here I report on an analysis of a maximum QF parameter and its uncertainty using mouse tumor induction data. Because experimental data for risks at low doses of γ-rays are highly uncertain which impacts estimates of maximum values of relative biological effectiveness (RBE max ), I developed an alternate QF model, denoted QF γAcute where QFs are defined relative to higher acute γ-ray doses (0.5 to 3 Gy). The alternate model reduces the dependence of risk projections on the DDREF, however a DDREF is still needed for risk estimates for high-energy protons and other primary or secondary sparsely ionizing space radiation components. Risk projections (upper confidence levels (CL)) for space missions show a reduction of about 40% (CL~50%) using the QF γAcute model compared the QFs based on RBE max and about 25% (CL~35%) compared to previous estimates. In addition, I discuss how a possible qualitative difference leading to increased tumor lethality for HZE particles compared to low LET radiation and background tumors remains a large uncertainty in risk estimates.
Oxidoreductase enzymes are widely used biocatalysts due to their high enantioselectivity and broad substrate compatibility in useful transformations. Many oxidoreductases require nicotinamide cofactors (i.e., NAD(P)H). To replace this costly natural cofactor, synthetic nicotinamide cofactor biomimetics (NCBs) offer different shapes, binding affinities, and reducing potentials that exceed the capabilities of wild-type NAD(P)H. However, the ill-defined structure–activity relationships (SARs) of various NCBs slow rationally guided innovation, such as customized reducing potentials. Here, we dissect two essential elements of NCB design, holding the nicotinamide invariant. First, the linker length between the nicotinamide and an unconjugated aromatic ring uncovered unexpected benefits to redox activity for two or three carbon linkers. Second, substitution on this unconjugated aryl group (Ring 2) might not be expected to affect activity. However, SAR trends demonstrate substantial benefits to reductive potential conferred by electron-donating functionalities on Ring 2. Furthermore, catalysis by two enzymes demonstrates enzyme-dependent tolerance or sensitivity to the NCB structures. Density functional theory (DFT) and computational modeling provide a theoretical framework to understand and build upon these observations. Ring 2 reaches up to the nicotinamide to stabilize its positive charge after oxidation through π–π stacking and charge transfer. Thus, the systematic examination of NCB’s stability, electrochemical redox potentials, and kinetics uncovers trends for the improved design of NCBs.
In recent decades, interest in plutonium mobility has increased significantly due to the need of the United States, as well as other nations, to deal with commercial spent nuclear fuel, nuclear weapons disarmament, and the remediation of locations contaminated by nuclear weapons testing and production. Although there is a global consensus that geologic disposal is the safest existing approach to dealing with spent nuclear fuel and high-level nuclear waste, only a few nations are moving towards implementing a geologic repository due to technical and political barriers. Understanding the factors that affect the mobility of plutonium in the subsurface environment is critical to support the development of such repositories. The importance of redox chemistry in determining plutonium mobility cannot be understated. While Pu(IV) is generally assumed to be immobile in the subsurface environment due to sorption or precipitation, Pu(V) tends to be mobile due to its relatively low effective charge and weak complex formation. This review highlights one particularly important aspect of plutonium behaviour at the mineral–water interface—the concept of surface-mediated reduction, which describes the reduction of plutonium on a mineral surface. It provides a conceptual model for and evidence supporting or refuting each proposed mechanism for surface-mediated reduction including (i) radiolysis at the mineral surface, (ii) electron transfer via ferrous iron or manganese in the mineral structure, (iii) electron shuttling due to the semiconducting properties of the mineral, (iv) disproportionation of Pu(V), (v) facilitation by proton exchange sites, (vi) stabilisation of Pu(IV) due to the increased concentration gradient within the electrical double layer, and (vii) a Nernstian favourability of Pu(IV) surface complexes and colloids. It also provides new perspectives on future research directions.
Here, we present here a model of carrier distribution and transport in semiconductor alloys accounting for quantum localization effects in disordered materials. This model is based on the recent development of a mathematical theory of quantum localization which introduces for each type of carrier a spatial function called localization landscape. These landscapes allow us to predict the localization regions of electron and hole quantum states, their corresponding energies, and the local densities of states. We show how the various outputs of these landscapes can be directly implemented into a drift-diffusion model of carrier transport and into the calculation of absorption/emission transitions. This creates a new computational model which accounts for disorder localization effects while also capturing two major effects of quantum mechanics, namely, the reduction of barrier height (tunneling effect) and the raising of energy ground states (quantum confinement effect), without having to solve the Schrödinger equation. Finally, this model is applied to several one-dimensional structures such as single quantum wells, ordered and disordered superlattices, or multiquantum wells, where comparisons with exact Schrödinger calculations demonstrate the excellent accuracy of the approximation provided by the landscape theory.