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At least 1,117 records · Page 62

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DOE OSTI2017

The leaching kinetics of cadmium from hazardous Cu-Cd zinc plant residues

Highlights: • A cleaner cadmium, zinc and copper recovery method from zinc plant waste residues was investigated. • The mechanisms and kinetics of cadmium recovery were discussed. • The effects of leaching variables were discussed. •The XRD and morphology analysis of raw residue and leaching residue were conducted. - Abstract: A large amount of Cu-Cd zinc plant residues (CZPR) are produced from the hydrometallurgical zinc plant operations. Since these residues contain substantial amount of heavy metals including Cd, Zn and Cu, therefore, they are considered as hazardous wastes. In order to realize decontamination treatment and efficient extraction of the valuable metals from the CZPR, a comprehensive recovery process using sulfuric acid as the leaching reagent and air as the oxidizing reagent has been proposed. The effect of temperature, sulfuric acid concentration, particle size, solid/liquid ratio and stirring speed on the cadmium extraction efficiency was investigated. The leaching kinetics of cadmium was also studied. It was concluded that the cadmium leaching process was controlled by the solid film diffusion process. Moreover, the order of the reaction rate constant versus H{sub 2}SO{sub 4} concentration, particle size, solid/liquid ratio and stirring speed was calculated. The XRD and SEM-EDS analysis results showed that the main phases of the secondary sulfuric acid leaching residues were lead sulfate and calcium sulfate.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Precision Measurement of the Microwave Dielectric Loss of Sapphire in the Quantum Regime with Parts-per-Billion Sensitivity

Dielectric loss is known to limit state-of-the-art superconducting qubit lifetimes. Recent experiments imply upper bounds on bulk dielectric loss tangents on the order of 100 parts per billion but because these inferences are drawn from fully fabricated devices with many loss channels, these experiments do not definitely implicate or exonerate the dielectric. To resolve this ambiguity, we devise a measurement method capable of separating and resolving bulk dielectric loss with a sensitivity at the level of 5 ×10 –9 . The method, which we call the dielectric dipper, involves the in situ insertion of a dielectric sample into a high-quality microwave cavity mode. Smoothly varying the participation of the sample in the cavity mode enables a differential measurement of the dielectric loss tangent of the sample. The dielectric dipper can probe the low-power behavior of dielectrics at cryogenic temperatures and does so without the need for any lithographic process, enabling controlled comparisons of substrate materials and processing techniques. We demonstrate the method with measurements of sapphire grown by edge-defined film-fed growth (EFG) in comparison to high-grade sapphire grown by the heat-exchanger method (HEMEX). For EFG sapphire, we infer a bulk loss tangent of 63⁢(8) ×10 –9 and a substrate-air interface loss tangent of 15⁢(3) ×10 –4 (assuming a sample surface thickness of 3 nm). For a typical transmon, this bulk loss tangent would limit device quality factors to Q ≲20 ×10 6 , suggesting that bulk loss is likely the dominant loss mechanism in the longest-lived transmons on sapphire. We also demonstrate this method on HEMEX sapphire and bound its bulk loss tangent to be less than 19⁢(6) ×10 –9 . As this bound is about 3 times smaller than the bulk loss tangent of EFG sapphire, the use of HEMEX sapphire as a substrate would lift the bulk dielectric coherence limit of a typical transmon qubit to several milliseconds.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

Handling debugger breakpoints in a shared instruction system

A debugger debugs processes that execute shared instructions so that a breakpoint set for one process will not cause a breakpoint to occur in the other processes. A breakpoint is set by recording the original instruction at the desired location and writing a trap instruction to the shared instructions at that location. When a process encounters the breakpoint, the process passes control to the debugger for breakpoint processing if the breakpoint was set at that location for that process. If the trap was not set at that location for that process, the cacheline containing the trap is copied to a small scratchpad memory, and the virtual memory mappings are changed to translate the virtual address of the cacheline to the scratchpad. The original instruction is then written to replace the trap instruction in the scratchpad, so that process can execute the instructions in the scatchpad thereby avoiding the trap instruction.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Systems and methods for control of polymer reactions and processing using automatic continuous online monitoring

Manual and automatic methods and devices using a ACOMP system for active control of polymerization reaction processes. An ideal desired trajectory of one or more reaction and polymer characteristics can be established to produce a desired final polymer product with specified characteristics from a polymerization reaction process. A current reaction trajectory of a polymerization reaction process can be driven to an ideal or desired reaction trajectory. In a manual embodiment an operator can use ACOMP data to adjust process variables in order to drive the current reaction trajectory toward the ideal or desired reaction trajectory. In an automated mode a control program can use ACOMP data to make adjustments to process variables to drive the polymerization reaction process toward the desired trajectory as closely as possible either empirically or by solving the governing equations for the polymerization reaction process.

Reed, Wayne Frederick↗

DOE OSTI2018

Control of Shell Morphology in p-n Heterostructured Water-Processable Semiconductor Colloids: Toward Extremely Efficient Charge Separation

This article describes p-n heterostructured water-borne semiconductor naonoparticles (NPs) with unique surface structures via control of shell morphology. The shell particles, comprising PC60-PC61BM composite, having n-type semiconductor characteristic, notably influence the charge carrier behavior in the core-shell NPs. A one- or two-phase methodology based on a PC60 surfactant-water phase and PC61BM n-type semiconductor-organic phase provided highly specific control over the shell structure of the NPs, which promoted their superior charge separation ability when combined with poly-3-hexyl-thiophene (P3HT). Moreover, the resulting water-borne NPs exhibit shell morphology-dependent carrier quenching and stability, which was characterized via luminescence studies paired with structural analysis. Corresponding to the results, outstanding performances of photovoltaic cells with over 5 % efficiency were achieved. The results suggest that the surrounding shell environments, such as the shell structure, and its electronic charge density, were crucial in determining the overall activity of the core-shell p-n heterostructured NPs. Thus, this work provides a new protocol in the current fields of water-based organic semiconductor colloids.

charge separation↗

DOE OSTI2019

A Highly Efficient Control Framework for Centralized Residential Charging Coordination of Large Electric Vehicle Populations

The potential for widespread adoption of plug-in electric vehicles (PEVs) brings with it the potential for negative impacts on the electric grid from electric vehicle charging. Uncoordinated PEV charging may increase electricity demand during peak hours, which could create concerns for the grid as the number of PEVs increases. Therefore, it is important to coordinate charging to alleviate potential negative impacts. Centralized charging coordination is preferred by grid operator over distributed control strategies because it can systematically allocate energy across a large population of PEVs and achieve global coordination benefits. However, centralized methods presented in the literature to date require prohibitively expensive computational resources and lack realistic PEV charging models. As a result, they cannot achieve the efficiency and accuracy required to implement charging coordination in the real world. This paper introduces a highly efficient receding horizon control framework that enables dynamic charging coordination for large PEV populations. A two-stage hierarchical optimization routine is proposed that aggregates individual PEV charging flexibility to reduce the computational complexity of the optimization process. The control framework is based on high-fidelity, validated charging system models and charging behavior models derived from a real-world data set of residential charging activities collected from thousands of charging stations over multiple years. Case studies illustrate that the proposed charging control framework is capable of effectively coordinating the charging of millions of PEVs using a standard desktop computer.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2014

LabVIEW-based control software for para-hydrogen induced polarization instrumentation

The elucidation of cell metabolic mechanisms is the modern underpinning of the diagnosis, treatment, and in some cases the prevention of disease. Para-Hydrogen induced polarization (PHIP) enhances magnetic resonance imaging (MRI) signals over 10 000 fold, allowing for the MRI of cell metabolic mechanisms. This signal enhancement is the result of hyperpolarizing endogenous substances used as contrast agents during imaging. PHIP instrumentation hyperpolarizes Carbon-13 ({sup 13}C) based substances using a process requiring control of a number of factors: chemical reaction timing, gas flow, monitoring of a static magnetic field (B{sub o}), radio frequency (RF) irradiation timing, reaction temperature, and gas pressures. Current PHIP instruments manually control the hyperpolarization process resulting in the lack of the precise control of factors listed above, resulting in non-reproducible results. We discuss the design and implementation of a LabVIEW based computer program that automatically and precisely controls the delivery and manipulation of gases and samples, monitoring gas pressures, environmental temperature, and RF sample irradiation. We show that the automated control over the hyperpolarization process results in the hyperpolarization of hydroxyethylpropionate. The implementation of this software provides the fast prototyping of PHIP instrumentation for the evaluation of a myriad of {sup 13}C based endogenous contrast agents used in molecular imaging.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

MODELLING OF ADDITIVE MANUFACTURING – COMPRESSION MOLDING PROCESS USING COMPUTATIONAL FLUID DYNAMICS

A computational fluid dynamics model has been developed to predict the behavior of a printed strands during a novel material extrusion additive manufacturing and compression molding process. While the traditional additive manufacturing process enables control over the fiber orientation within the part, it would also result in high void content. On the other hand, compression molding produces parts with low porosity levels at rapid processing cycle time but lacks control over the microstructure. The novel additive manufacturing – compression molding (AM-CM) integrating both these processes offers control over both the microstructure and porosity to manufacturing high performance composite parts. The numerical model developed here enables to analyze the effect of processing parameters on the behaviour of printed layer that is subsequently compressed and to determine the optimal printing parameters for high-performance composite part design.

Seta, Berin↗

DOE OSTI2022

Gaussian process for calibration and control of GlueX Central Drift Chamber

We have developed and implemented a machine learning based system to calibrate and control the GlueX Central Drift Chamber at Jefferson Lab, VA, in near real-time. The system monitors environmental and experimental conditions during data taking and uses those as inputs to a Gaussian process (GP) with learned prior. The GP predicts calibration constants in order to recommend a high voltage (HV) setting for the detector that maintains consistent detector performance (gain and resolution) throughout data taking. This approach is in stark contrast to traditional detector operations in which the detector operates at fixed HV and its calibration parameters vary quite considerably with time. Additionally, the ML based system utilizes uncertainty quantification to correct the recommended control parameters when appropriate. We will present results from the ML system autonomously during the Charged Pion Polarizability (CPP) experiment conducted in Hall D at Jefferson Lab.

McSpadden, Helen↗

DOE OSTI2022

Gaussian process for calibration and control of GlueX Central Drift Chamber

McSpadden, Helen↗

DOE OSTI2019

What do we know about soil carbon destabilization?

Abstract Most empirical and modeling research on soil carbon (C) dynamics has focused on those processes that control and promote C stabilization. However, we lack a strong, generalizable understanding of the mechanisms through which soil organic carbon (SOC) is destabilized in soils. Yet a clear understanding of C destabilization processes in soil is needed to quantify the feedbacks of the soil C cycle to the Earth system. Destabilization includes processes that occur along a spectrum through which SOC shifts from a ‘protected’ state to an ‘available’ state to microbial cells where it can be mineralized to gaseous forms or to soluble forms that are then lost from the soil system. These processes fall into three general categories: (1) release from physical occlusion through processes such as tillage, bioturbation, or freeze-thaw and wetting-drying cycles; (2) C desorption from soil solids and colloids; and (3) increased C metabolism. Many processes that stabilize soil C can also destabilize C, and C gain or loss depends on the balance between competing reactions. For example, earthworms may both destabilize C through aggregate destruction, but may also create new aggregates and redistribute C into mineral horizon. Similarly, mycorrhizae and roots form new soil C but may also destabilize old soil C through priming and promoting microbial mining; labile C inputs cause C stabilization through increased carbon use efficiency or may fuel priming. Changes to the soil environment that affect the solubility of minerals or change the relative surfaces charges of minerals can destabilize SOC, including increased pH or in the reductive dissolution of Fe-bearing minerals. By considering these different physical, chemical, and biological controls as processes that contribute to soil C destabilization, we can develop thoughtful new hypotheses about the persistence and vulnerability of C in soils and make more accurate and robust predictions of soil C cycling in a changing environment.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2011

Optimization of processing parameters on the controlled growth of ZnO nanorod arrays for the performance improvement of solid-state dye-sensitized solar cells

High-transparency and high quality ZnO nanorod arrays were grown on the ITO substrates by a two-step chemical bath deposition (CBD) method. The effects of processing parameters including reaction temperature (25-95 {sup o}C) and solution concentration (0.01-0.1 M) on the crystal growth, alignment, optical and electrical properties were systematically investigated. It has been found that these process parameters are critical for the growth, orientation and aspect ratio of the nanorod arrays, showing different structural and optical properties. Experimental results reveal that the hexagonal ZnO nanorod arrays prepared under reaction temperature of 95 {sup o}C and solution concentration of 0.03 M possess highest aspect ratio of {approx}21, and show the well-aligned orientation and optimum optical properties. Moreover the ZnO nanorod arrays based heterojunction electrodes and the solid-state dye-sensitized solar cells (SS-DSSCs) were fabricated with an improved optoelectrical performance. -- Graphical abstract: The ZnO nanorod arrays demonstrate well-alignment, high aspect ratio (L/D{approx}21) and excellent optical transmittance by low-temperature chemical bath deposition (CBD). Display Omitted Research highlights: > Investigate the processing parameters of CBD on the growth of ZnO nanorod arrays. > Optimization of CBD process parameters: 0.03 M solution concentration and reaction temperature of 95 {sup o}C. > The prepared ZnO samples possess well-alignment and high aspect ratio (L/D{approx}21). > An n-ZnO/p-NiO heterojunction: great rectifying behavior and low leakage current. > SS-DSSC has J{sub SC} of 0.31 mA/cm{sup 2} and V{sub OC} of 590 mV, and an improved {eta} of 0.059%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

HEXIM1 controls P-TEFb processing and regulates drug sensitivity in triple-negative breast cancer

The positive transcription elongation factor b (P-TEFb), composed of CDK9 and cyclin T, stimulates transcriptional elongation by RNA polymerase (Pol) II and regulates cell growth and differentiation. Recently, we demonstrated that P-TEFb also controls the expression of EMT regulators to promote breast cancer progression. In the nucleus, more than half of P-TEFb are sequestered in the inactive-state 7SK snRNP complex. Here, we show that the assembly of the 7SK snRNP is preceded by an intermediate complex between HEXIM1 and P-TEFb that allows transfer of the kinase active P-TEFb from Hsp90 to 7SK snRNP for its suppression. Down-regulation of HEXIM1 locks P-TEFb in the Hsp90 complex, keeping it in the active state to enhance breast cancer progression, but also rendering the cells highly sensitive to Hsp90 inhibition. Because HEXIM1 is often down-regulated in human triple-negative breast cancer (TNBC), these cells are particularly sensitive to Hsp90 inhibition. Our study provides a mechanistic explanation for the increased sensitivity of TNBC to Hsp90 inhibition.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2011

Hydrological parameter estimations from a conservative tracer test with variable-density effects at the Boise Hydrogeophysical Research Site

Reliable predictions of groundwater flow and solute transport require an estimation of the detailed distribution of the parameters (e.g., hydraulic conductivity, effective porosity) controlling these processes. However, such parameters are difficult to estimate because of the inaccessibility and complexity of the subsurface. In this regard, developments in parameter estimation techniques and investigations of field experiments are still challenging and necessary to improve our understanding and the prediction of hydrological processes. Here we analyze a conservative tracer test conducted at the Boise Hydrogeophysical Research Site in 2001 in a heterogeneous unconfined fluvial aquifer. Some relevant characteristics of this test include: variable-density (sinking) effects because of the injection concentration of the bromide tracer, the relatively small size of the experiment, and the availability of various sources of geophysical and hydrological information. The information contained in this experiment is evaluated through several parameter estimation approaches, including a grid-search-based strategy, stochastic simulation of hydrological property distributions, and deterministic inversion using regularization and pilot-point techniques. Doing this allows us to investigate hydraulic conductivity and effective porosity distributions and to compare the effects of assumptions from several methods and parameterizations. Our results provide new insights into the understanding of variabledensity transport processes and the hydrological relevance of incorporating various sources of information in parameter estimation approaches. Among others, the variable-density effect and the effective porosity distribution, as well as their coupling with the hydraulic conductivity structure, are seen to be significant in the transport process. The results also show that assumed prior information can strongly influence the estimated distributions of hydrological properties.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Intelligent Experiments Through Real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and Future EIC Detectors (Final Report)

The overall vision of this project was to integrate real-time artificial intelligence (AI) directly into the data acquisition and detector-control systems of nuclear physics experiments, including both fast online event selection and an autonomous detector-control feedback loop. The work carried out under the award focused on the fast online event-selection half of that vision: the efficient recording of low-momentum heavy-flavor (HF) hadron decays in proton-proton collisions at the sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC)—an observable that requires fast tracking and topological trigger selection not previously demonstrated at RHIC, and that is essential for QCD studies at future facilities such as the Electron-Ion Collider (EIC). The autonomous detector-control (GPU-based feedback) component named in the project title remained a design concept and was not implemented under this award. The Massachusetts Institute of Technology (MIT) group led the offline simulation and data processing needed to train the machine-learning (ML) models, the translation of trained models to Field-Programmable Gate Array (FPGA) firmware using the hls4ml framework, and the physics validation of heavy-flavor reconstruction. Over the award period, the team developed and hardware-tested the principal components of an AI-based heavy-flavor trigger on simulated and recorded sPHENIX tracker data: a software Bipartite Graph Attention Network (BiGAT) trigger model reaching > 95% signal efficiency at 99% background rejection; an FPGA-native hit clusterizer matching the offline clustering; smaller networks synthesized to FPGA within the required sub-10 µs latency; and an assembled decoder–clusterizer–inference firmware chain exercised on the FELIX readout board. A complete, fully integrated hardware demonstrator was not finished within the award period. This report documents the project goals, the MIT group’s contributions, the technical accomplishments, and the outlook toward applications at the future EIC ePIC detector.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2013

Phase II Nevada Water Resources Data, Modeling, and Visualization (DMV) Center (Final Report)

Water is unquestionably a critical resource throughout the United States. In the semi-arid west -- an area stressed by increase in human population and sprawl of the built environment -- water is the most important limiting resource. Crucially, science must understand factors that affect availability and distribution of water. To sustain growing consumptive demand, science needs to translate understanding into reliable and robust predictions of availability under weather conditions that could be average but might be extreme. These predictions are needed to support current and long-term planning. Similar to the role of weather forecast and climate prediction, water prediction over short and long temporal scales can contribute to resource strategy, governmental policy and municipal infrastructure decisions, which are arguably tied to the natural variability and unnatural change to climate. Change in seasonal and annual temperature, precipitation, snowmelt, and runoff affect the distribution of water over large temporal and spatial scales, which impact the risk of flooding and the groundwater recharge. Anthropogenic influences and impacts increase the complexity and urgency of the challenge. The goal of this project has been to develop a decision support framework of data acquisition, digital modeling, and 3D visualization. This integrated framework consists of tools for compiling, discovering and projecting our understanding of processes that control the availability and distribution of water. The framework is intended to support the analysis of the complex interactions between processes that affect water supply, from controlled availability to either scarcity or deluge. The developed framework enables DRI to promote excellence in water resource management, particularly within the Lake Tahoe basin. In principle, this framework could be replicated for other watersheds throughout the United States. Phase II of this project builds upon the research conducted during Phase I, in which the hydrologic framework was investigated and the development initiated. Phase II concentrates on practical implementation of the earlier work but emphasizes applications to the hydrology of the Lake Tahoe basin. Phase 1 efforts have been refined and extended by creating a toolset for geographic information systems (GIS) that is usable for disparate types of geospatial and geo-referenced data. The toolset is intended to serve multiple users for a variety of applications. The web portal for internet access to hydrologic and remotely sensed product data, prototyped in Phase I, has been significantly enhanced. The portal provides high performance access to LANDSAT-derived data using techniques developed during the course of the project. The portal is interactive, and supports the geo-referenced display of hydrologic information derived from remotely sensed data, such as various vegetative indices used to calculate water consumption. The platform can serve both internal and external constituencies using inter-operating infrastructure that spans both sides of the DRI firewall. The platform is intended grow its supported data assets and to serve as a template for replication to other geographic areas. An unanticipated development during the project was the use of ArcGIS software on a new computer system, called the IBM PureSytems, and the parallel use of the systems for faster, more efficient image processing. Additional data, independent of the portal, was collected within the Sagehen basin and provides detailed information regarding the processes that control hydrologic responses within mountain watersheds. The newly collected data include elevation, evapotranspiration, energy balance and remotely sensed snow-pack data. A Lake Tahoe basin hydrologic model has been developed, in part to help predict the hydrologic impacts of climate change. The model couples both the surface and subsurface hydrology, with the two components having been independently calibrated. Results from the coupled simulations involving both surface water and groundwater processes show that it is possible to fairly accurately simulate lake effects and water budget variables over a wide range of dry and wet cycles in the historical record. The Lake Tahoe basin is representative of the hydrology, topography and climate throughout the Sierra Nevada Range, and the entire model development is prototypical of the efforts required to replicate the decision support framework to other locales. The Lake Tahoe model in particular, could allow water managers to evaluate more accurately components of the water budget (ET, runoff, groundwater, etc) and to answer important questions regarding water resources in northern Nevada. This report discusses the geographic scale and the hydrologic complexity of the calibrated model developed as part of this project, as well as simulation results for historical and future climate projects To enable human-driven data exploration and discovery, de novo software for a globalized rendering module that extends the capability of our evolving custom visualization engine from Phase I (called SMEngine) has been developed. The new rendering component, called Horizon, supports terrain rendering capable of displaying and interrogating both remotely sensed and modeled data. The development of Horizon necessitated adaptation of the visualization engine to allow extensible integration of components such as the global rendering module and support for associated features. The resulting software is general in its GIS capability, but a specific Lake Tahoe visualization application suitable for immersive decision support in the DRIVE6 virtual reality facility has been developed. During the development, various features to enhance the value of the visualization experience were explored, including the use of hyperspectral image overlays. An over-arching goal of the visualization aspect of the project has been to develop and demonstrate the CAVE (CAVE Automatic Virtual Environment) as a practical tool for hydrologic research.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Controlled Nucleation and Growth Process of Li 2 S 2 /Li 2 S in Lithium-Sulfur Batteries

Lithium-sulfur battery is a promising next-generation energy storage system because of its potentially three to five times higher energy density than that of traditional lithium ion batteries. However, the dissolution and precipitation of soluble polysulfides during cycling initiate a series of key-chain reactions that significantly shorten battery life. Herein, we demonstrate that through a simple but effective strategy, significantly improved cycling performance is achieved for high sulfur loading electrodes through controlling the nucleation and precipitation of polysulfieds on the electrode surface. More than 400 or 760 stable cycling are successfully displayed in the cells with locked discharge capacity of 625 mAh g -1 or 500 mAh g -1 , respectively. The nucleation and growth process of dissolved polysulfides has been electrochemically altered to confine the thickness of discharge products passivated on the cathode surface, increasing the utilization rate of sulfur while avoiding severe morphology changes on the electrode. More importantly, the exposure of new lithium metal surface to the S-containing electrolyte is also greatly reduced through this strategy, largely minimizing the anode corrosion caused by polysulfides. This work interlocks the electrode morphologies and its evolution with electrochemical interference to modulate cell performances by using Li-S system as a platform, providing different but critical directions for this community.

25 ENERGY STORAGE↗

DOE OSTI2011

Weak Convergence and Fluid Limits in Optimal Time-to-Empty Queueing Control Problems

We consider a class of controlled queue length processes, in which the control allocates each server's effort among the several classes of customers requiring its service. Served customers are routed through the network according to (prescribed) routing probabilities. In the fluid rescaling, X{sup n}(t) = 1/nX(nt) , we consider the optimal control problem of minimizing the integral of an undiscounted positive running cost until the first time that X{sup n}=0. Our main result uses weak convergence ideas to show that the optimal value functions V{sup n} of the stochastic control problems for X{sup n}(t) converge (as n{yields}{infinity}) to the optimal value V of a control problem for the limiting fluid process. This requires certain equicontinuity and boundedness hypotheses on (V{sup n}). We observe that these are essentially the same hypotheses that would be needed for the Barles-Perthame approach in terms of semicontinuous viscosity solutions. Sufficient conditions for these equicontinuity and boundedness properties are briefly discussed.

97 MATHEMATICS AND COMPUTING↗