Developing a National Structural Complexity Database for U.S. Saline Basins
For presentation at the 2023 FECM/NETL Carbon Management Research Project Review Meeting, Pittsburgh, PA, August 28-September 1, 2023.
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For presentation at the 2023 FECM/NETL Carbon Management Research Project Review Meeting, Pittsburgh, PA, August 28-September 1, 2023.
Many knowledge based software generation methods have been proposed to improve software quality and programmer productivity. Several government and industry initiatives have focused on software reusability as one solution to these problems. DARTS (trademark), a General Dynamics proprietary symbolic processing technology, provides a unique solution to the reuse problem: archtyping. Archtyping is the embedding of high order language statements in text files. An advanced macroprocessor uses the text files to generate new versions of complex software systems. A DARTS program, the Software Generation and Configuration Management (SGCM) System automates the archtyping process and maintenance cycle. The DARTS technology is briefly discussed, archtyping is described, and the SGCM system is presented in detail.
This paper reports our investigation of flight path monitoring in aviation. We interviewed experienced pilots to understand the knowledge and skills underlying effective monitoring and we developed an example learning environment to improve these skills. We explore how design of pilot training and learning, like the design of interfaces and of the underlying automation, benefits from cognitive engineering methods and perspective. In aviation, monitoring and managing flight path are critical activities. The influences on flight path are complex and come from the autoflight system, from control actions by the pilot, and from external factors, including weather and Air Traffic Control (ATC). Indeed, inadequate flight path monitoring is a current aviation concern as it has been implicated in accidents and incidents. Effective piloting depends on strategies for noticing, understanding, and anticipating these influences to monitor and manage flight path. Lack of such skills reduces pilots' ability to maintain safety margin and resilience. Although flightdeck automation is intended to aid pilot understanding and prediction, the Fight Management Systems (FMS) can mislead as well as aid the pilot's understanding and projection of what will happen. In dynamic conditions, FMS predictions may be based on old or incomplete information. Understanding such vulnerabilities is an important part of pilot-autoflight coordination. The learning environment we developed is designed to help pilots proactively monitor and manage flight path. We consider how a broad cognitive engineering approach might inform the "what" and "how" of learning in dynamic work domains.
As the power density of electric machines and power electronics continues to increase to meet the demands of more electric aircraft, the thermal management of these devices becomes increasingly important. Ideally, the thermal management solution of the device should have high thermal conductivity and be electrically insulating so that it can be directly integrated with the device in question. Technical ceramics are a class of materials that meet these two requirements. Direct liquid cooling by submerging electric components in a dielectric fluid is an alternate option, but adds system complexity and may incur pumping loss. In this work, the thermal management solution for a high frequency inductor is presented. A conventional wicked heat pipe is designed that is made from a solid ceramic case with a sintered ceramic wick. This heat pipe can provide structural support for the core and windings and is electrically insulating, so it does not incur any additional eddy current losses from the high frequency magnetic fields. It does not require additional pumping power, because conventional wicked heat pipes are passive devices. In this paper, the manufacturing process of the ceramic heat pipe is also presented. It is shown that the sintering of large diameter spherical ceramic particles is difficult due to their high specific surface area and low surface free energy. To overcome this difficulty, a flux material was used to initiate liquid phase sintering. The results of the sintering trials show that for the 120 μm diameter α-Al2O3powder selected for the wick, the combination of 1650°C sintering temperature and the addition of 5 wt% talc sintered the porous matrix together sufficiently for use as a heat pipe wic
As the power density of electric machines and power electronics continues to increase to meet the demands of more electric aircraft, the thermal management of these devices becomes increasingly important. Ideally, the thermal management solution of the device should have high thermal conductivity and be electrically insulating so that it can be directly integrated with the device in question. Technical ceramics are a class of materials that meet these two requirements. Direct liquid cooling by submerging electric components in a dielectric fluid is an alternate option, but adds system complexity and may incur pumping loss. In this work, the thermal management solution for a high frequency inductor is presented. A conventional wicked heat pipe is designed that is made from a solid ceramic case with a sintered ceramic wick. This heat pipe can provide structural support for the core and windings and is electrically insulating, so it does not incur any additional eddy current losses from the high frequency magnetic fields. It does not require additional pumping power, because conventional wicked heat pipes are passive devices. In this paper, the manufacturing process of the ceramic heat pipe is also presented. It is shown that the sintering of large diameter spherical ceramic particles is difficult due to their high specific surface area and low surface free energy. To overcome this difficulty, a flux material was used to initiate liquid phase sintering. The results of the sintering trials show that for the 120 μm diameter α-Al2O3 powder selected for the wick, the combination of 1650°C sintering temperature and the addition of 5 wt% talc sintered the porous matrix together sufficiently for use as a heat pipe wick.
Automated fault management is at the forefront of next-generation optical communication networks. The increase in complexity of modern networks has triggered the need for programmable and software-driven architectures to support the operation of agile and self-managed systems. In these scenarios, the European Telecommunications Standards Institute zero-touch network and service management approach is imperative. The need for machine learning algorithms to process the large volume of telemetry data brings safety concerns as distributed cloud-computing solutions become the preferred approach for deploying reliable communication network automation. This paper’s contribution is twofold. First, we propose a simple yet effective method to guarantee the confidentiality of the telemetry data based on feature scrambling. The method allows the operation of third-party computational services without direct access to the full content of the collected data. Additionally, the effectiveness of four unsupervised machine learning algorithms for soft-failure detection is evaluated when applied to the scrambled telemetry data. The methods are based on factor analysis, principal component analysis, nonlinear principal component analysis, and singular value decomposition. Most dimensionality reduction algorithms have the common property that they can maintain similar levels of fault classification performance while hiding the data structure from unauthorized access. Evaluations of the proposed algorithms demonstrate this capability.
Management of spent nuclear fuel and high-level radioactive waste consists of three main phases – storage, transportation, and disposal – commonly referred to as the back end of the nuclear fuel cycle. Current practice for commercial spent nuclear fuel management in the United States (US) includes temporary storage of spent fuel in both pools and dry storage systems at operating or shutdown nuclear power plants. Storage pools are filling to their operational capacity, and management of the approximately 2,200 metric tons of spent fuel newly discharged each year requires transferring older and cooler spent fuel from pools into dry storage. Unless a repository becomes available that can accept spent fuel for permanent disposal, projections indicate that the US will have approximately 136,000 metric tons of spent fuel in dry storage systems by mid-century, when the last plants in the current reactor fleet are decommissioned. Current designs for dry storage systems rely on large multi-assembly canisters, the most common of which are so-called “dual-purpose canisters” (DPCs). DPCs are certified for both storage and transportation, but are not designed or licensed for permanent disposal. The large capacity (greater number of spent fuel assemblies) of these canisters can lead to higher canister temperatures, which can delay transportation and/or complicate disposal. This current management practice, in which the utilities continue loading an ever-increasing inventory of larger DPCs, does not emphasize integration among storage, transportation, and disposal. This lack of integration does not cause safety issues, but it does lead to a suboptimal system that increases costs, complicates storage and transportation operations, and limits options for permanent disposal. This paper describes strategies for improving integration of management practices in the US across the entire back end of the nuclear fuel cycle. The complex interactions between storage, transportation, and disposal make a single optimal solution unlikely. However, efforts to integrate various phases of nuclear waste management can have the greatest impact if they begin promptly and continue to evolve throughout the remaining life of the current fuel cycle. A key factor that influences the path forward for integration of nuclear waste management practices is the identification of the timing and location for a repository. The most cost-effective path forward would be to open a repository by mid-century with the capability to directly dispose of DPCs without repackaging the spent fuel into disposalready canisters. Options that involve repackaging of spent fuel from DPCs into disposalready canisters or that delay the repository opening significantly beyond mid-century could add 10s of billions of dollars to the total system life cycle cost.
The Knowledge Management Information Tool (KM-IT) is a web-based system developed to maintain and preserve the Department of Energy's (DoE's) knowledge base. The system was developed by Florida International University's Applied Research Center (FIU-ARC) with the support of the D and D community including the DOE Office of Environmental Management, and with the collaboration and support of the DoE's Energy Facility Contractors Group (EFCOG) and the former ALARA Centers at Hanford and Savannah. The KM-IT system is a community driven system tailored to serve the technical issues faced by the workforce across the DOE Complex. This KM-IT web-based interactive system is operational and available for use at www.dndkm.org and is currently comprised of the following modules: Web Crawler, Hotline, Technology, Hanford's ALARA Center Reports, Specialist Directory, Lessons Learned, Best Practices, Video/Picture Library, Vendors and Industry News. The Web Crawler dynamically searches through the KM-IT repository as well as the web and displays search results based on the search criteria. The Hotline allows registered users to post questions/problems related to D and D and to receive solutions from a subject-matter specialist. The Technology module serves as repository of D and D technologies and contains technology/ demonstration fact sheets and vendor information. D and D community members can add Lessons Learned, Best Practices, and Pictures/Videos to the D and D repository, after a formal approval process. The Vendor module provides a directory of commercial vendors who provide D and D related technologies, supplies, and services. KM-IT makes an excellent use of the knowledge that exists within the D and D community by allowing D and D project managers around the DOE complex to collaborate by sharing innovative ideas, past experiences, and practices and by maintaining a directory of subject matter specialists. FIU has developed the dedicated module on KM-IT platform to publish D and D research being performed at FIU. This module highlights current EM research efforts and activities in support of D and D being performed at FIU/SRNL associated with fixatives and intumescent products. FIU will expand this module to include the recent and current D and D research being performed across multiple DOE EM sites, national labs and universities. FIU will collaborate with SRNL, INL, ANL and other universities to explore and publish D and D research activities on KM-IT. As a result, the user community will have a centralized location to review new D and D related research across the DOE EM complex. (authors)
This review synthesizes methods for measuring, modeling, and managing hydrologic connectivity, offering pathways to improve practices and address environmental challenges (e.g., climate change) and sustainability. As a key driver of water movement and nutrient cycling, hydrologic connectivity influences flood mitigation, water quality regulation, and biodiversity conservation. However, traditional field-based methods (e.g., dye tracing), indirect measurements (e.g., runoff analysis), and remote sensing techniques (e.g., InSAR) often struggle to capture the complexity of catchment-scale interactions. Similarly, modeling approaches—including process-based and percolation theory-based models, graph theory, and entropy-based metrics—face limitations in fully representing these interconnected processes. Both modeling and measurement techniques are constrained by inadequate spatial and temporal coverage, high data demands, computational complexity, and difficulties in representing subsurface connectivity. Subsequently, we critique current management practices that prioritize isolated variables (e.g., streamflow, sediment transport) over system-wide strategies and emphasize the need for adaptive, connectivity-based approaches in water resource planning and restoration. Moving forward, we highlight the importance of interdisciplinary collaboration, technological innovations (e.g., AI-driven modeling, real-time monitoring), and integrated frameworks to improve connectivity measurement, modeling, and adaptive management to restore fragmented hydrologic networks. This integrated approach sets the stage for transformative water resource management, fostering proactive policy development and stakeholder engagement.
The Space Infrared Telescope Facility (SIRTF) was launched in August, 2003, and renamed to the Spitzer Space Telescope in 2004. Two years of observing the universe in the wavelength range from 3 to 180 microns has yielded enormous scientific discoveries. Since this magnificent observatory has a limited lifetime, maximizing science viewing efficiency (ie, maximizing time spent executing activities directly related to science observations) was the key operational objective. The strategy employed for maximizing science viewing efficiency was to optimize spacecraft flexibility, adaptability, and use of observation time. The selected approach involved implementation of a multi-engine sequencing architecture coupled with nondeterministic spacecraft and science execution times. This approach, though effective, added much complexity to uplink operations and sequence development. The Jet Propulsion Laboratory (JPL) manages Spitzer s operations. As part of the uplink process, Spitzer s Mission Sequence Team (MST) was tasked with processing observatory inputs from the Spitzer Science Center (SSC) into efficiently integrated, constraint-checked, and modeled review and command products which accommodated the complexity of non-deterministic spacecraft and science event executions without increasing operations costs. The MST developed processes, scripts, and participated in the adaptation of multi-mission core software to enable rapid processing of complex sequences. The MST was also tasked with developing a Downlink Keyword File (DKF) which could instruct Deep Space Network (DSN) stations on how and when to configure themselves to receive Spitzer science data. As MST and uplink operations developed, important lessons were learned that should be applied to future missions, especially those missions which employ command-intensive operations via a multi-engine sequence architecture.
Regardless of the mission type: deep space or low Earth orbit, robotic or human spaceflight, Fault Management (FM) is a critical aspect of NASA space missions. As the complexity of space missions grows, the complexity of supporting FM systems increase in turn. Data on recent NASA missions show that development of FM capabilities is a common driver for significant cost overruns late in the project development cycle. Efforts to understand the drivers behind these cost overruns, spearheaded by NASA's Science Mission Directorate (SMD), indicate that they are primarily caused by the growing complexity of FM systems and the lack of maturity of FM as an engineering discipline. NASA can and does develop FM systems that effectively protect mission functionality and assets. The cost growth results from a lack of FM planning and emphasis by project management, as well the maturity of FM as an engineering discipline, which lags behind the maturity of other engineering disciplines. As a step towards controlling the cost growth associated with FM development, SMD has commissioned a multi-institution team to develop a practitioner's handbook representing best practices for the end-to-end processes involved in engineering FM systems. While currently concentrating primarily on FM for science missions, the expectation is that this handbook will grow into a NASA-wide handbook, serving as a companion to the NASA Systems Engineering Handbook. This paper presents a snapshot of the principles that have been identified to guide FM development from cradle to grave. The principles range from considerations for integrating FM into the project and SE organizational structure, the relationship between FM designs and mission risk, and the use of the various tools of FM (e.g., redundancy) to meet the FM goal of protecting mission functionality and assets.
Many high-performance systems now include different types of memory devices within the same compute platform to meet strict performance and cost constraints. Such heterogeneous memory systems often include an upper-level tier with better performance, but limited capacity, and lower-level tiers with higher capacity, but less bandwidth and longer latencies for reads and writes. To utilize the different memory layers efficiently, current systems rely on hardware-directed, memory -side caching or they provide facilities in the operating system (OS) that allow applications to make their own data-tier assignments. Since these data management options each come with their own set of trade-offs, many systems also include mixed data management configurations that allow applications to employ hardware- and software-directed management simultaneously, but for different portions of their address space. Despite the opportunity to address limitations of stand-alone data management options, such mixed management modes are under-utilized in practice, and have not been evaluated in prior studies of complex memory hardware. In this work, we develop custom program profiling, configurations, and policies to study the potential of mixed data management modes to outperform hardware- or software-based management schemes alone. Our experiments, conducted on an Intel ® Knights Landing platform with high-bandwidth memory, demonstrate that the mixed data management mode achieves the same or better performance than the best stand-alone option for five memory intensive benchmark applications (run separately and in isolation), resulting in an average speedup compared to the best stand-alone policy of over 10 %, on average.
ed systems and the procedures for ng in complexity. This interacting trend places a larger burden on pilots to manage increasing amounts of information and to understand system interactions. The result is an increase in the likelihood of loss of airplane state awareness (ASA). One way to gain more insight into this issue is through experimentation using objective measures of visual behavior. This study summarizes an analysis of oculometer data obtained during a high-fidelity flight simulation study that included a variety of complex pilot-system interactions that occur in current flight decks, as well as several planned for the next generation air transportation system. The study was comprised of various scenarios designed to induce low and high energy aircraft states coupled with other emulated causal factors in recent accidents. Three different display technologies were evaluated in this recent pilot-in-the-loop study conducted at NASA Langley Research Center. These technologies include a stall recovery guidance algorithm and display concept, an enhanced airspeed control indication of when the automation is no longer actively controlling airspeed, and enhanced synoptic diagrams with corresponding simplified electronic interactive checklists. Multiple data analyses were performed to understand how the 26 participating airline pilots were observing ASA-related information provided during different stag specific events within these stages.
Abstract Avoiding over-pressurization in subsurface reservoirs is critical for applications like CO $$_2$$ 2 sequestration and wastewater injection. Managing the pressures by controlling injection/extraction are challenging because of complex heterogeneity in the subsurface. The heterogeneity typically requires high-fidelity physics-based models to make predictions on CO $$_2$$ 2 fate. Furthermore, characterizing the heterogeneity accurately is fraught with parametric uncertainty. Accounting for both, heterogeneity and uncertainty, makes this a computationally-intensive problem challenging for current reservoir simulators. To tackle this, we use differentiable programming with a full-physics model and machine learning to determine the fluid extraction rates that prevent over-pressurization at critical reservoir locations. We use DPFEHM framework, which has trustworthy physics based on the standard two-point flux finite volume discretization and is also automatically differentiable like machine learning models. Our physics-informed machine learning framework uses convolutional neural networks to learn an appropriate extraction rate based on the permeability field. We also perform a hyperparameter search to improve the model’s accuracy. Training and testing scenarios are executed to evaluate the feasibility of using physics-informed machine learning to manage reservoir pressures. We constructed and tested a sufficiently accurate simulator that is 400 000 times faster than the underlying physics-based simulator, allowing for near real-time analysis and robust uncertainty quantification.
Recent NASA missions have required software systems that are larger, more complex, and more critical than NASA software systems of the past. The Ada programming language and the software methods and support environments associated with it are seen as potential breakthroughs in meeting NASA's software requirements. The findings of a study by the Ada and Software Management Assessment Working Group (ASMAWG) are presented. The study was chartered to perform three tasks: (1) assess the agency's ongoing and planned Ada activities; (2) assess the infrastructure (standards, policies, and internal organizations) supporting software management and the Ada activities; and (3) present an Ada implementation and use strategy appropriate for NASA over the next 5 years.
When combining data from distinct sources, there is a need to share meta-data and other knowledge about various source domains. Due to semantic inconsistencies and heterogeneity of representations, problems arise in combining multiple domains when the domains are merged. The knowledge that is irrelevant to the task of interoperation will be included, making the result unnecessarily complex. This heterogeneity problem can be eliminated by mediating the conflicts and managing the intersections of the domains. For interoperation and intelligent access to heterogeneous information, the focus is on the intersection of the knowledge, since intersection will define the required articulation rules. An algebra over domain has been proposed to use articulation rules to support disciplined manipulation of domain knowledge resources. The objective of a domain algebra is to provide the capability for interrogating many domain knowledge resources, which are largely semantically disjoint. The algebra supports formally the tasks of selecting, combining, extending, specializing, and modifying Components from a diverse set of domains. This paper presents a domain algebra and demonstrates the use of articulation rules to link declarative interfaces for Internet and enterprise applications. In particular, it discusses the articulation implementation as part of a production system capable of operating over the domain described by the IDL (interface description language) of objects registered in multiple CORBA servers.
The subject of this paper is a NASA research program, known as the Coolant Flow Management Program, which focuses on the interaction between the internal coolant channel and the external film cooling of a turbine blade and/or vane in an aircraft gas turbine engine. The turbine gas path is really a very complex flow field. The combination of strong pressure gradients, abrupt geometry changes and intersecting surfaces, viscous forces, rotation, and unsteady blade/vane interactions all combine to offer a formidable challenge. To this, in the high pressure turbine, we add the necessity of film cooling. The ultimate goal of the turbine designer is to maintain or increase the high level of turbine performance and at the same time reduce the amount of coolant flow needed to achieve this end. Simply stated, coolant flow is a penalty on the cycle and reduces engine thermal efficiency. Accordingly, understanding the flow field and heat transfer associated with the coolant flow is a priority goal. It is important to understand both the film cooling and the internal coolant flow, particularly their interaction. Thus, the motivation for the Coolant Flow Management Program. The paper will begin with a brief discussion of the management and research strategy, will then proceed to discuss the current attack from the internal coolant side, and will conclude by looking at the film cooling effort - at all times keeping sight of the primary goal the interaction between the two. One of the themes of this paper is that complex heat transfer problems of this nature cannot be attacked by single researchers or even groups of researchers, each working alone. It truly needs the combined efforts of a well-coordinated team to make an impact. It is important to note that this is a government/industry/university team effort.
We report that more than a 60% increase in crop production is required by the 2050's to feed a growing world population. Understanding how plant functional traits and field management affect crop yields has the potential to improve agricultural productivity, minimize economic and environmental losses, and maximize food security. We explored the influence of winter wheat root characteristics and management on winter wheat growth, yield, and profit using a mechanistic and well-tested ecosystem and crop model, ecosys. We applied and further tested ecosys at an agricultural farm growing winter wheat in Ardmore, Oklahoma, United States. The model accurately predicted observed shoot carbon (R 2 = 0.95), soil moisture (R 2 = 0.67), soil temperature (R 2 = 0.91), and yield (percent error = 17%). Numerical optimization experiments were conducted to explore potential improvements of winter wheat yield and profit by modifying root characteristics, including root radius and root:shoot carbon transfer conductance, and fertilizer inputs. Our results show the potential for simultaneously improving winter wheat yields and profits. The optimum conditions were found to be in the range of root radius between 0.1 and 0.3 mm, carbon transfer conductance between 0.004 and 0.01 h -1 , and the currently applied fertilizer rate of 112 kg ha -1 . Under these conditions, improvements in yields and profits of up to approximately 25% and 110%, respectively, were modeled compared to those under baseline root traits. These improvements were achieved by impoverishing root structures, thereby increasing nutrient allocation to grains. Our results also demonstrate and motivate model structures that integrate the complex network of plant physiology, soil nutrient biogeochemistry, hydrology, and management.