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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Combustion Performance and Emissions Optimization through Integration of Miniaturized High Temperature Multi Process Monitoring System

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings. The mMPMS is based on an electrochemical sensor that provides a real-time indication of the risk of damage to key locations in the radiant or convective section of a coal-fired boiler such as metal loss rates, heat flux, metal surface temperature, and deposit thickness. These indications can be utilized to optimize boiler performance as well as improve boiler availability in conjunction with corresponding operating conditions. This monitoring system was developed and tested in the high-temperature regions of coal-fired utility boilers in this project but can be applied to many other industries and applications as well. The new sensor design, leveraging the existing electrochemical noise-based monitoring system, is small enough to be installed through the webbing of the waterwalls without the need for long shut-downs to bend tubes and to make it feasible to obtain high spatial resolution in the boiler. Data can be transferred to the plant distributed control system (DCS) and any other control system. The sensor body that houses the sensor assembly was designed to ensure good conductive contact with boiler tubes to ensure the sensor is held at an identical temperature to the tube surface temperature. The data acquisition and signal conditioning modules were redesigned into a small footprint with optimized cooling of the module. System software was developed specifically for the new signal conditioning module and is compatible with plant PLCs. After the preliminary testing at a pilot-scale facility, five mMPMS were installed at a full-scale pulverized coal-fired plant, Basin Electric Power Cooperative’s Leland Olds Unit 1. The systems were demonstrated over a 6-week period during typical operation. Sensor measurements of deposit thickness were validated during the demonstration and subsequently leveraged to determine sensor-based boiler cleaning strategies. These strategies have the benefit of reduced thermal stresses on boiler tubes from over-cleaning and improved boiler water management. At the end of the project, continued development of the sensor technology was carried out at PacifiCorp’s Hunter Station. REI leveraged the permanent installation of the mMPMS in Unit 3 made possible by DOE funding on a separate program. The work at Hunter Plant focused on application of machine learning and artificial intelligence-based models for integration of sensor signals into control and optimization of Hunter Unit 3 processes.

Advanced Sensors, Corrosion, Ash Deposition, Optim↗
NASA NTRS2010

Cassini Titan Science Integration: Getting a 'Jumpstart' on the Process

The Cassini spacecraft has been in orbit for five years, returning a wealth of scientific data from Titan and the Saturn system. The mission is a cooperative undertaking between NASA, ESA and the Italian Space Agency and the project is currently planning for a second extension of the mission. The Cassini Solstice Mission (CSM) will extend the mission's lifetime until Saturn's northern summer solstice in 2017. The Titan Orbiter Science Team (TOST) has the task of integrating the science observations for all 126 targeted Titan flybys (44 in the Prime Mission, 26 in the first extension (Equinox Mission), and 56 in the second extension (Solstice Mission)) contained in the chosen trajectory. Cassini science instruments are body-fixed with limited ability to articulate; thus, the spacecraft pointing during the flybys must be allocated among the instruments to accomplish the mission's science goals. The science that can be accomplished on each Titan flyby also critically depends on the closest approach altitude, which is in turn determined by the attitude, but changing the altitude impacts the overall trajectory for the Solstice Mission. During the Prime and Extended missions, TOST has learned that the best way to achieve Cassini's Titan science goals is via a 'jumpstart' process prior to final delivery of the trajectory. The jumpstart is driven by the desire to balance Titan science across the entire set of flybys during the CSM, and to influence any changes (tweaks) to the flyby altitudes. By the end of the jumpstart, TOST produces Master Timelines for each flyby, identifying each flyby's prime science observations and allocating control of the spacecraft attitude to specific instrument teams. In addition, developing timelines early, while the science and operations teams are still fully funded, decreases the future workload in integration and implementation.

Steadman, Kimberly B.↗
NASA NTRSDate not supplied

Demonstration of How Manufacturing Innovations Challenge Conventional Structural Design

For almost 100 years, commercial aircraft have been fabricated using riveted aluminum alloy structures. Aside from refining aircraft designs for better aerodynamic efficiency, improving alloy compositions, and automating assembly steps, fuselage construction remains largely unchanged today. The intent of the lightweight metallic fuselage prototype undertaken in NASA’s Advanced Air Transport Technology project was to demonstrate innovative forming and joining processes that advance the design paradigm, i.e. achieve high-rate manufacturing and reduce assembly time/costs. Over the past decade, researchers at NASA Langley Research Center have evaluated the potential to modify the flow forming process to produce near-net shaped cylinders, integrally stiffened along the cylinder axis, for space launch vehicles. The production of integral stiffeners in a formed aluminum cylinder, the size of the Space Shuttle external tank, replaced machined thick plate and welding steps to eliminate > 500,000 pounds of machining chips and ~ 0.5 miles of welds. The flow forming method, called the Integrally Stiffened Cylinder (ISC) process, was successfully demonstrated up to the 10-foot diameter scale, which laid the groundwork for the current investigation of metallic fuselage structures. Using the ISC process as the basis for the re-design of a metallic fuselage eliminates hundreds of thousands of holes and rivets, while significantly reducing assembly time and crack initiation sites in the integral structure. However, the ISC process is not currently configured to fabricate circumferential ring frames for carrying fuselage internal pressure loads. Consequently, a trade study was performed to assess existing and advanced manufacturing processes, including additive manufacturing, forming, and welding. The approach with the lowest barriers to success, while simultaneously improving manufacturing time and cost, was to use formed ring frame segments attached to the ISC via Refill Friction Stir Spot Welding (RFSSW). The RFSSW process is five times faster than drilling, reaming, and riveting and provides similar mechanical performance. Finishing the fuselage structure with conventional windows, floor beams, and floor panels can then be accomplished using incumbent assembly methods, thereby maximizing reuse of existing infrastructure for aircraft construction. Structural analyses were performed to assess and optimize the geometric variables of integrated skin and stiffener configurations. A cost benefit and manufacturing rate analysis was also performed to compare against the current state-of-the-art for single aisle transport class aircraft. The resulting structure offers a weight reduction that rivals current graphite-epoxy composite fuselage structures. The projected manufacturing rate is close to double current metallic fuselages and six times faster than current composite manufacturing practices. The damage tolerance properties of a monocoque fuselage structure have yet to be assessed, but past integral airframe structural work has exploited geometric features to blunt or turn cracks. This concept offers promise that integrated structures can meet stringent aircraft durability specifications. An important benefit is that such aluminum fuselage structures may be inspected and repaired using established practices and existing expertise. Finally, pursuit of advanced manufacturing processes for future aluminum fuselages minimizes waste and the structure is 100% recyclable at the end-of-life for maximum sustainability.

aluminum↗
DOE OSTI2023

Design of an Integrated Solids Handling System to Maximize Syngas Process Reliability (Cooperative Research and Development Final Report)

The National Renewable Energy Laboratory (NREL), in partnership with Wonderful Renewable Energy (WRE) and Idaho National Laboratory (INL), plans to develop a general methodology for designing integrated biorefinery solids preprocessing, handling, and feeding systems based on the chemical, physical, and mechanical attributes of the starting biomass material. This attribute-driven approach will include detailed feedstock property measurements, iterative computational modeling, and bench-scale testing to design systems for preprocessing, handling, and reactor in-feed, up to and including the selection of the conversion reactor. The initial tests and system design will be conducted using waste material from almond and pistachio growing and production operations (shells, hulls, and wood), targeting the conversion of this material to syngas for electricity production. The methodology will then be generalized to other feedstocks. The purpose of this project is to design an integrated solids handling system to maximize the process reliability of converting almond and pistachio waste to electricity. The design methodology and workflow developed from this example will then be applied to the Feedstock Conversion Interface Consortium (FCIC) benchmark loblolly pine residues, thus demonstrating the robustness of the overall design approach and providing insight and guidance for future conversion systems. V-Grid Energy Systems was brought on as a subcontractor to provide gasifiers and labor to complete gasifier runs.

09 BIOMASS FUELS↗
NASA NTRS2016

Cost-Benefit Analysis for the Advanced Near Net Shape Technology (ANNST) Method for Fabricating Stiffened Cylinders

This cost-benefit analysis assesses the benefits of the Advanced Near Net Shape Technology (ANNST) manufacturing process for fabricating integrally stiffened cylinders. These preliminary, rough order-of-magnitude results report a 46 to 58 percent reduction in production costs and a 7-percent reduction in weight over the conventional metallic manufacturing technique used in this study for comparison. Production cost savings of 35 to 58 percent were reported over the composite manufacturing technique used in this study for comparison; however, the ANNST concept was heavier. In this study, the predicted return on investment of equipment required for the ANNST method was ten cryogenic tank barrels when compared with conventional metallic manufacturing. The ANNST method was compared with the conventional multi-piece metallic construction and composite processes for fabricating integrally stiffened cylinders. A case study compared these three alternatives for manufacturing a cylinder of specified geometry, with particular focus placed on production costs and process complexity, with cost analyses performed by the analogy and parametric methods. Furthermore, a scalability study was conducted for three tank diameters to assess the highest potential payoff of the ANNST process for manufacture of large-diameter cryogenic tanks. The analytical hierarchy process (AHP) was subsequently used with a group of selected subject matter experts to assess the value of the various benefits achieved by the ANNST method for potential stakeholders. The AHP study results revealed that decreased final cylinder mass and quality assurance were the most valued benefits of cylinder manufacturing methods, therefore emphasizing the relevance of the benefits achieved with the ANNST process for future projects.

Stoner, Mary Cecilia↗
NASA NTRS1994

Simplifying operations with an uplink/downlink integration toolkit

The Operations Engineering Lab (OEL) at JPL has developed a simple, generic toolkit to integrate the uplink/downlink processes, (often called closing the loop), in JPL's Multimission Ground Data System. This toolkit provides capabilities for integrating telemetry verification points with predicted spacecraft commands and ground events in the Mission Sequence Of Events (SOE) document. In the JPL ground data system, the uplink processing functions and the downlink processing functions are separate subsystems that are not well integrated because of the nature of planetary missions with large one-way light times for spacecraft-to-ground communication. Our new closed-loop monitoring tool allows an analyst or mission controller to view and save uplink commands and ground events with their corresponding downlinked telemetry values regardless of the delay in downlink telemetry and without requiring real-time intervention by the user. An SOE document is a time-ordered list of all the planned ground and spacecraft events, including all commands, sequence loads, ground events, significant mission activities, spacecraft status, and resource allocations. The SOE document is generated by expansion and integration of spacecraft sequence files, ground station allocations, navigation files, and other ground event files. This SOE generation process has been automated within the OEL and includes a graphical, object-oriented SOE editor and real-time viewing tool running under X/Motif. The SOE toolkit was used as the framework for the integrated implementation. The SOE is used by flight engineers to coordinate their operations tasks, serving as a predict data set in ground operations and mission control. The closed-loop SOE toolkit allows simple, automated integration of predicted uplink events with correlated telemetry points in a single SOE document for on-screen viewing and archiving. It automatically interfaces with existing real-time or non real-time sources of information, to display actual values from the telemetry data stream. This toolkit was designed to greatly simplify the user's ability to access and view telemetry data, and also provide a means to view this data in the context of the commands and ground events that are used to interpret it. A closed-loop system can prove especially useful in small missions with limited resources requiring automated monitoring tools. This paper will discuss the toolkit implementation, including design trade-offs and future plans for enhancing the automated capabilities.

Murphy, Susan C.↗
NASA NTRS2009

A New View of Radiation-Induced Cancer: Integrating Short- and Long-Term Processes. Part II: Second Cancer Risk Estimation

As the number of cancer survivors grows, prediction of radiotherapy-induced second cancer risks becomes increasingly important. Because the latency period for solid tumors is long, the risks of recently introduced radiotherapy protocols are not yet directly measurable. In the accompanying article, we presented a new biologically based mathematical model, which, in principle, can estimate second cancer risks for any protocol. The novelty of the model is that it integrates, into a single formalism, mechanistic analyses of pre-malignant cell dynamics on two different time scales: short-term during radiotherapy and recovery; long-term during the entire life span. Here, we apply the model to nine solid cancer types (stomach, lung, colon, rectal, pancreatic, bladder, breast, central nervous system, and thyroid) using data on radiotherapy-induced second malignancies, on Japanese atomic bomb survivors, and on background US cancer incidence. Potentially, the model can be incorporated into radiotherapy treatment planning algorithms, adding second cancer risk as an optimization criterion.

Shuryak, Igor↗
NASA NTRS2015

Thermal Radiometer Signal Processing Using Radiation Hard CMOS Application Specific Integrated Circuits for Use in Harsh Planetary Environments

Thermal radiometers such as proposed for the Europa Clipper flyby mission require low noise signal processing for thermal imaging with immunity to Total Ionizing Dose (TID) and Single Event Latchup (SEL). Described is a second generation Multi- Channel Digitizer (MCD2G) Application Specific Integrated Circuit (ASIC) that accurately digitizes up to 40 thermopile pixels with greater than 50 Mrad (Si) immunity TID and 174 MeV-sq cm/mg SEL. The MCD2G ASIC uses Radiation Hardened By Design (RHBD) techniques with a 180 nm CMOS process node.

Focal Plane Assembly↗
DOE OSTI2026

Continental-Scale Controls on Hyporheic Respiration Revealed by Knowledge-Guided Machine Learning

Hyporheic zone sediments regulate organic matter turnover and in-stream respiration, yet controls on sediment respiration remain poorly constrained across heterogeneous river networks, limiting prediction of stream metabolism and carbon processing at continental scales. Here, we integrate observations from ~90 river corridors across the United States in the WHONDRS consortium with a knowledge-guided machine learning (KGML) framework that couples thermodynamic rate theory with machine learning to identify dominant controls on hyporheic respiration. Diagnostic analyses show that organic matter concentration and thermodynamic favorability define an upper bound on respiration potential, whereas biological catalytic capacity and physical accessibility jointly govern realized respiration rates through interaction effects. To represent unmeasurable accessibility constraints, we use the mechanistic model as a scaffold for KGML, allowing machine learning to target residual structure not explained by process theory. This hybrid framework improves predictive skill relative to both the mechanistic model alone and fully data-driven models while preserving interpretability. These results indicate that variability in hyporheic respiration is largely mechanistically structured and demonstrate how integrating process theory with explainable AI enhances predictive performance while enabling scalable synthesis of river corridor observations.

Zheng, Jianqiu↗
DOE OSTI2022

Local Thermomechanical Processing for Improving Formability of High Strength Aluminum Sheets

Limited room temperature formability hinders the wide-spread use of high strength aluminum alloys in structural body-in-white parts. Stamping or extrusion at warm temperatures or from softer tempers are the current solutions. In this work, our approach is to start with age-hardened sheets from 7xxx and 6xxx family of alloys and improve their formability using local thermomechanical processing only in the regions demanding highest ductility in the forming processes. We achieved local formability improvements with friction stir processing and introduce another process named roller-bending as a concept and showed its feasibility through finite element simulations. Initial results from FSP indicated significant deformation in the processed zones with minimal sheet distortion. FSP also resulted in dynamically recrystallized, fine grained (d < 5 µm) microstructures in the processed regions with textures significantly different from the base material. This resulted in formability improvements of > 30% in 7085-T76 and > 50% in 6111-T6 alloys as measured by minimum bend radius (r/t) ratios established with V-bending tests performed at 90° and 180° bend angles. Based on the encouraging initial results, we envision applicability of these processes in both pre- and post-stamping stages through integration of the process tools as end-effectors to robotic arms.

Nasim, Wahaz↗
NASA NTRS1994

VLSI technology for smaller, cheaper, faster return link systems

Very Large Scale Integration (VLSI) Application-specific Integrated Circuit (ASIC) technology has enabled substantially smaller, cheaper, and more capable telemetry data systems. However, the rapid growth in available ASIC fabrication densities has far outpaced the application of this technology to telemetry systems. Available densities have grown by well over an order magnitude since NASA's Goddard Space Flight Center (GSFC) first began developing ASIC's for ground telemetry systems in 1985. To take advantage of these higher integration levels, a new generation of ASIC's for return link telemetry processing is under development. These new submicron devices are designed to further reduce the cost and size of NASA return link processing systems while improving performance. This paper describes these highly integrated processing components.

Nanzetta, Kathy↗
NASA NTRS2002

Bi-Level Integrated System Synthesis (BLISS) for Concurrent and Distributed Processing

The paper introduces a new version of the Bi-Level Integrated System Synthesis (BLISS) methods intended for optimization of engineering systems conducted by distributed specialty groups working concurrently and using a multiprocessor computing environment. The method decomposes the overall optimization task into subtasks associated with disciplines or subsystems where the local design variables are numerous and a single, system-level optimization whose design variables are relatively few. The subtasks are fully autonomous as to their inner operations and decision making. Their purpose is to eliminate the local design variables and generate a wide spectrum of feasible designs whose behavior is represented by Response Surfaces to be accessed by a system-level optimization. It is shown that, if the problem is convex, the solution of the decomposed problem is the same as that obtained without decomposition. A simplified example of an aircraft design shows the method working as intended. The paper includes a discussion of the method merits and demerits and recommendations for further research.

Sobieszczanski-Sobieski, Jaroslaw↗
DOE OSTI2023

Scalable aqueous-phase fabrication of reduced graphene oxide nanofiltration membranes by an integrated roll-to-roll (R2R) process

Economic fractionation of multicomponent biomass-derived streams is a key challenge in biobased fuels and chemicals production. Kraft black liquor (BL) is generated at ~1 billion tons/yr globally from biomass pulping and contains ~15wt% total solids including lignin, hemicellulose fragments, and inorganics. Membrane-based BL concentration is attractive but challenged by low solute rejections and poor stability in BL, which combines alkaline pH (~13), high dissolved solids content (15+ wt%) and high temperature (70–85°C). Here we discuss the scaled fabrication and characterization of reduced graphene oxide (rGO) nanofiltration membranes by slot die coating on a roll-to-roll (R2R) with integrated vacuum filtration. Here, we obtain high-quality 90×30 cm rGO membranes (referred to as “R2R-rGO membranes” in this work) with ~100 nm average thickness supported on porous poly(ethersulfone) (PES) sheets, and an effective area of 2700cm 2 . We present characterizations of their microstructure and uniformity as mapped over large areas by scanning electron microscopy (SEM), ellipsometry, adhesion test and X-ray photoelectron spectroscopy (XPS). The constructed ellipsometry model for the rGO membrane/PES substrate composite was successfully applied to 48 different locations of the R2R-rGO membranes. The R2R-rGO membranes showed >98% lignin rejection with a steady state flux of ~12 LMH at 50bar in a 15.7wt% total solids (TS) kraft BL stream at 72°C and 2–3 gal/min crossflow rates. Slot die coating on a R2R platform with integrated vacuum filtration can enable rapid fabrication of high-quality GO membranes at scale without organic solvents or volatile organic compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Optimization on Manifolds via Graph Gaussian Processes

This paper integrates manifold learning techniques within a Gaussian process upper confidence bound algorithm to optimize an objective function on a manifold. Our approach is motivated by applications where a full representation of the manifold is not available and querying the objective is expensive. We rely on a point cloud of manifold samples to define a graph Gaussian process surrogate model for the objective. Query points are sequentially chosen using the posterior distribution of the surrogate model given all previous queries. We establish regret bounds in terms of the number of queries and the size of the point cloud. Several numerical examples complement the theory and illustrate the performance of our method.

Bayesian optimization↗
DOE OSTI2020

Conceptual Basis and Techno-Economic Modeling for Integrated Algal Biorefinery Conversion of Microalgae to Fuels and Products (2019 NREL TEA Update: Highlighting Paths to Future Cost Goals via a New Pathway for Combined Algal Processing)

The report documents the conceptual basis for a new potential Combined Algal Processing design strategy which may allow more flexibility in accommodating different algal biomass feedstock compositions, by enabling upgrading of both protein and carbohydrates in a single step, without a strict requirement for either component to be in soluble or monomeric form, while maintaining effective wet lipid extraction techniques to enable high lipid recoveries. In light of previously-established constraints around algal biomass costs (which are significantly higher than lignocellulosic terrestrial biomass), the present CAP processing strategy reflects an integrated biorefinery concept producing both fuels and value-added chemical coproducts as a means to improve profitability and generate coproduct revenues to help drive down the minimum fuel selling price (MFSP) towards economically viable levels. Namely, this report highlights an integrated CAP biorefinery process and associated technical targets that would be required to achieve U.S. Department of Energy target MFSP goals of $2.5/gallon gasoline equivalent by 2030. This is accomplished by a process involving low-cost seasonal storage of algal biomass during high-growth seasons, rapid flash hydrolysis pretreatment of the biomass, solvent extraction of pretreated biomass, cleanup and fractionation of lipids into triglyceride and free fatty acid fractions, and a series of thermochemical conversion steps to upgrade carbohydrates and protein to hydrocarbon fuels. These steps include mild oxidative treatment (MOT), a process originally investigated at NREL for upgrading lignin, followed by catalytic ketonization and hydrotreating of MOT products to fuels. Isolated triglycerides are sent to a coproduct train, with the base case focused on upgrading to polyurethane foams as a high-value, high-market-volume coproduct.

09 BIOMASS FUELS↗
DOE OSTI2025

Accelerating Discovery of Solid‐State Thin‐Film Metal Dealloying for 3D Nanoarchitecture Materials Design through Laser Thermal Gradient Treatment

Thin‐film solid‐state metal dealloying (thin‐film SSMD) is a promising method for fabricating nanostructures with controlled morphology and efficiency, offering advantages over conventional bulk materials processing methods for integration into practical applications. Although machine learning (ML) has facilitated the design of dealloying systems, the selection of key thermal treatment parameters for nanostructure formation remains largely unknown and dependent on experimental trial and error. To overcome this challenge, a workflow enabling high‐throughput characterization of thermal treatment parameters is demonstrated using a laser‐based thermal treatment to create temperature gradients on single thin‐film samples of Nb‐Al/Sc and Nb‐Al/Cu. This continuous thermal space enables observation of dealloying transitions and the resulting nanostructures of interest. Through synchrotron X‐ray multimodal and high‐throughput characterization, critical transitions and nanostructures can be rapidly captured and subsequently verified using electron microscopy. The key temperatures driving chemical reactions and morphological evolutions are clearly identified. While the oxidation may influence nanostructure formation during thin‐film treatment, the dealloying process at the dealloying front involves interactions solely between the dealloying elements, highlighting the availability and viability of the selected systems. Further, this approach enables efficient exploration of the dealloying process and validation of ML predictions, thereby accelerating the discovery of thin‐film SSMD systems with targeted nanostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Automated electrosynthesis reaction mining with multimodal large language models (MLLMs)

Leveraging the chemical data available in legacy formats such as publications and patents is a significant challenge for the community. Automated reaction mining offers a promising solution to unleash this knowledge into a learnable digital form and therefore help expedite materials and reaction discovery. However, existing reaction mining toolkits are limited to single input modalities (text or images) and cannot effectively integrate heterogeneous data that is scattered across text, tables, and figures. In this work, we go beyond single input modalities and explore multimodal large language models (MLLMs) for the analysis of diverse data inputs for automated electrosynthesis reaction mining. We compiled a test dataset of 65 articles (MERMES-T24 set) and employed it to benchmark five prominent MLLMs against two critical tasks: (i) reaction diagram parsing and (ii) resolving cross-modality data interdependencies. The frontrunner MLLM achieved ≥96% accuracy in both tasks, with the strategic integration of single-shot visual prompts and image pre-processing techniques. We integrate this capability into a toolkit named MERMES (multimodal reaction mining pipeline for electrosynthesis). Our toolkit functions as an end-to-end MLLM-powered pipeline that integrates article retrieval, information extraction and multimodal analysis for streamlining and automating knowledge extraction. This work lays the groundwork for the increased utilization of MLLMs to accelerate the digitization of chemistry knowledge for data-driven research.

Leong, Shi Xuan↗
NASA NTRS1995

Integrated planning and scheduling for Earth science data processing

Several current NASA programs such as the EOSDIS Core System (ECS) have data processing and data management requirements that call for an integrated planning and scheduling capability. In this paper, we describe the experience of applying advanced scheduling technology operationally, in terms of what was accomplished, lessons learned, and what remains to be done in order to achieve similar successes in ECS and other programs. We discuss the importance and benefits of advanced scheduling tools, and our progress toward realizing them, through examples and illustrations based on ECS requirements. The first part of the paper focuses on the Data Archive and Distribution (DADS) V0 Scheduler. We then discuss system integration issues ranging from communication with the scheduler to the monitoring of system events and re-scheduling in response to them. The challenge of adapting the scheduler to domain-specific features and scheduling policies is also considered. Extrapolation to the ECS domain raises issues of integrating scheduling with a product-generation planner (such as PlaSTiC), and implementing conditional planning in an operational system. We conclude by briefly noting ongoing technology development and deployment projects being undertaken by HTC and the ISTB.

Boddy, Mark↗