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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 523 records · Page 29

Effects of Mn content on the deformation behavior of Fe-Mn-Al-C TWIP steels — A computational study

This paper presents a double-slip/double-twin polycrystal plasticity model using finite element solution to investigate the kinetics of deformation twinning of low-to-medium manganese (Mn) twinning-induced plasticity (TWIP) steels. Empirical equations are employed to estimate the stacking fault energy (SFE) of TWIP steels and the critical resolved shear stress (CRSS) for dislocation slip and deformation twinning, respectively. The results suggest that the evolution of twinning in Fe-xMn-1.4Al-0.6C (x=11.5, 13.5, 15.5, 17.5 and 19.5) TWIP steels, and its relation to the Mn content, can explain the effect of Mn on mechanical properties.the stress-strain. By comparing the double-slip/double-twin model to a double-slip model, the predicted results essentially reveal that the interaction behavior between dislocation slip and deformation twinning can lead to an additional work hardening. Also, numerical simulations are carried out to study the influence of boundary conditions on deformation behavior and twin formation. The nucleation and growth of twinning are found to depend on internal properties (e.g., mismatch orientation of grains and stress redistribution) as well as on external constraints (e.g., the applied boundary conditions) of the material.

Wang, Yuan↗

Adoption of AI in the Utility T&D Sector: Use Cases, Consequence, Assessment and Benefits

Digital transformation and utilization of artificial intelligence (AI) in the electric grid are fundamentally changing the industry’s approach to common problems and enabling a broader paradigm shift in grid planning and operations. The change in approach is circularly both enabling and driving modernization, with load growth and reliable management of data center and AI infrastructure shifting away from planning approaches with relatively predictable behaviors and toward a mix of consumer and industrial choices that surpass human cognitive abilities to process. This movement has potential to condition humans to not understand the system on which the AI depends, while requiring it for development of the necessary infrastructure. Approaches which would address most likely grid conditions and events, such as faults, aging of equipment, and weather, now must also account for large loads which shift not based upon weather or time of day, but the computational load. Quantifying computational load is independent of the traditional grid forecasting variables, where a data center’s aggregate load is determined by user and AI system behavior and decoupled from normal grid planning and operations. AI is both the cause and solution for these challenges, with new grid planning tools integrating massive amounts of decisions into frameworks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Atomic faulting drives exceptional toughness in low thermal expansion chromium alloys

Endowing functional properties with mechanical responses in traditional metals has been a frontier topic, akin to transforming base metal into gold. Chromium and its alloys, with their functional deficiencies and limited ductility, serve as typical examples. Herein, we report a Cr96Fe4Ge1.3B1 alloy that unifies low thermal expansion (LTE, αl = 1.79 × 10-6 K-1, 200 − 315 K) with exceptional toughness (240.2 J·cm-3). The enhancement in mechanical responses is primarily attributed to layered Cr2B intermetallic precipitates, which ameliorate interfacial cohesion and simultaneously refine the grain structure. The weakened interlayer interactions within the Cr-B layers facilitate the nucleation and movement of numerous tiny stacking faults in precipitates, efficiently alleviating strain energy and resulting in marked work-hardening ability. Additionally, antiferromagnetic fluctuations in the BCC matrix contribute to the unique LTE behavior. This paves the way for the design of high-performance alloys featuring layered-symmetry precipitates.

Yu, Chengyi [University of Science and Technology ↗

The effect of boron addition on the deformation behavior and microstructure of β-solidify TiAl alloys

Highlights: • Borides could promote the DRX formation to soften TiAl alloys. • Boron addition increases firstly and then stabilizes the deformation activate energy. • The stable region expands with boron increasing in processing maps. • The DRX critical strain increases firstly and then decreases with boron increasing. • DRX softening and strengthening from solid solution and borides influence deformation behavior. - Abstract: The effect of boron addition on the deformation behavior and microstructure of Ti-43Al-6Nb-1Mo -1Cr alloys have been studied in this paper. Boron addition would induce Ti{sub 2}Al(P6{sub 3}/mmc) phase with hexagonal structure formation on the interfaces between TiB and γ phase. TiB would be the obstacles for dislocations slipping and increase the stacking fault energy. Ti{sub 2}Al could also provide the chemical foundation for DRXed γ nucleation and disappear after thermal deformation. Both these two phase could promote DRXed grains nucleation to soften the alloys during thermal deformation. With the strengthen effect of boron solid solution and TiB obstacles, the microstructure evolution, phase transformation and deformation behavior are also discussed and concluded as follow.

36 MATERIALS SCIENCE↗

Hardware Verification and Validation for a Navigation Sensor Software Model in Support of Flight Vehicle Performance Analysis

… or, “It’s in the details, how to make complicated software perform like complicated hardware.” In attempts to minimize development time and quickly build an operational vehicle, NASA’s Space Launch System (SLS) has had to be intentional about integrated testing. Constraints on budget and schedule have required balance between testing needs and the desire for an integrated flight vehicle as soon as possible. To provide key insights early in design and analysis cycles, a large amount of effort has shifted into maturing and validating models at the component level with integrated testing as a means to validate their integration. In terms of SLS Navigation, this, and the model-based design approach have pushed explicit requirements for sensor models to be validated against flight hardware to high precision. This paper covers the approach taken to verify and validate the models for the two key navigation sensors on the SLS vehicle, the Redundant Inertial Navigation Sensor and the Rate Gyro Assembly. These models are used in performance evaluation, fault detection, and operations development extensively. Using a mix of data from hardware vendor documentation and testing reports, limited in-house testing, and integration activities, these models were able to be validated against flight hardware at multiple levels, from the internal software design to statistical behavior at the raw sensor and integrated box levels. The high level of insight into the hardware elements is instrumental to support flight certification activities and building confidence in SLS Navigation capability. Focused testing enabled additional insight and validation that proved invaluable and the resulting insights were used to focus and mature models. Additionally, of having validated performance-based hardware models enables a wide breadth of activities including detailed fault detection studies and integration into future vehicle frameworks, such as an upper stage and provide a valuable asset to continued SLS analysis and design.

Evan J Anzalone↗

Hardware Verification and Validation for a Navigation Sensor Software Model in Support of Flight Vehicle Performance Analysis

… or, “It’s in the details, how to make complicated software perform like complicated hardware.” In attempts to minimize development time and quickly build an operational vehicle, NASA’s Space Launch System (SLS) has had to be intentional about integrated testing. Constraints on budget and schedule have required balance between testing needs and the desire for an integrated flight vehicle as soon as possible. To provide key insights early in design and analysis cycles, a large amount of effort has shifted into maturing and validating models at the component level with integrated testing as a means to validate their integration. In terms of SLS Navigation, this, and the model-based design approach have pushed explicit requirements for sensor models to be validated against flight hardware to high precision. This paper covers the approach taken to verify and validate the models for the two key navigation sensors on the SLS vehicle, the Redundant Inertial Navigation Sensor and the Rate Gyro Assembly. These models are used in performance evaluation, fault detection, and operations development extensively. Using a mix of data from hardware vendor documentation and testing reports, limited in-house testing, and integration activities, these models were able to be validated against flight hardware at multiple levels, from the internal software design to statistical behavior at the raw sensor and integrated box levels. The high level of insight into the hardware elements is instrumental to support flight certification activities and building confidence in SLS Navigation capability. Focused testing enabled additional insight and validation that proved invaluable and the resulting insights were used to focus and mature models. Additionally, of having validated performance-based hardware models enables a wide breadth of activities including detailed fault detection studies and integration into future vehicle frameworks, such as an upper stage and provide a valuable asset to continued SLS analysis and design.

Thomas Park↗

Analyzing impact of $\mathrm{DER}$ on $\mathrm{FIDVR}$ - comparison of $\mathrm{EMT}$ simulation of a combined transmission and distribution grid with aggregated positive sequence models

The increase in percentage of distributed energy resources (DERs) brings in a degree of uncertainty in bulk power system planning and operations. Further, the presence of 1 - φ induction motors introduces the possibility of motor stalling and fault induced delayed voltage recovery (FIDVR). With newer versions of IEEE Std 1547™ there can be the opportunity to obtain dynamic voltage support from DERs. In this report, the impact of DERs providing dynamic voltage on the dynamic behavior of 1 - φ induction motors is examined in detail along with an exploration of the need for simulation platforms that go beyond positive sequence. The studies discussed here are carried out both in detailed electromagnetic time domain and in positive sequence domain for comparison.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Strain-driven oxygen vacancy ordering in LaNiO 3 thin films revealed by integrated differential phase contrast imaging in scanning transmission electron microscopy

Rare-earth nickelates, such as LaNiO 3 (LNO), exhibit complex electronic properties, with ordered oxygen vacancies (OOV) influencing conductivity and magnetic behavior. We investigate the structural stability of strain-induced OOV phases in LNO thin films grown on SrTiO 3 substrates and the impact of Ruddlesden–Popper (RP) faults. Using high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and integrated differential phase contrast (iDPC) STEM imaging, we conducted atomic-scale structural and compositional analyses of OOV. Geometric phase analysis (GPA) was employed to measure the strain in fault-free and RP fault regions, while density functional theory (DFT) calculations explored different OOV arrangements in the LNO phase. Simulated iDPC-STEM imaging of energy-stabilized structures was performed to correlate with experimental results. Here, our findings reveal superstructure modulation in the chemical composition and atomic-scale lattice structure in LNO, primarily due to the formation of the OOV in Ni–O layers of the LaNiO 2.5 phase. The out-of-plane compressive strain of about 2% stabilizes this phase, reducing the strain, diminishing OOV, and transforming them into LNO.

36 MATERIALS SCIENCE↗

Center for Frontiers of Subsurface Energy Security (Final Report)

For the past two decades a slowly growing consensus has been that rising temperature is being caused by increases in carbon dioxide (CO 2 ) in the Earth’s atmosphere. What is less consensual is what to do about it. Solutions range from reducing emissions to various ways to capture CO 2 (from effluents of power plants, as plants, etc.) and store it away from the atmosphere. The problem is of such magnitude that it is likely that we will need many methods. Also some methods would cause draconian harm to global economies. This work is about the storage part of the reducing of CO 2 in the atmosphere. There have been many methods proposed for storing CO 2 : in vegetation, at the bottom of oceans, in land farms, and in subsurface formations. The latter is particularly prominent given the large estimated volume in porous formation in the Earth, and the 50-year old experience in injecting CO 2 for enhanced oil recovery. This report is about the science behind subsurface storage, called here geological carbon storage or GCS. Effective GCS requires that billions of metric tons of CO 2 be injected into storage reservoirs annually. GCS feasibility requires balancing the opposing impacts of large emplacement (injection) rates without compromising caprock seal integrity during injection. Once injected, the challenge is to assure the injected CO 2 remains permanently stored. Under most conditions, CO 2 is in a supercritical state, or scCO 2 . scCO 2 is immiscible with the subsurface brine and has a factor of ten smaller viscosity, leading to the development of two-phase fluid flow and scCO 2 bypassing. After the injection of large volumes of scCO 2 , the pore pressure, state of stress, chemical, thermal, and biological steady-state or equilibrium conditions in the subsurface are disrupted, which may lead to unpredictable behavior because the responses to these changes are often non-linear. Current challenges for efficient and reliable scCO 2 storage are: (1) sustaining large injection rates; (2) using available pore space efficiently, and (3) controlling undesired or unexpected behavior, such as scCO 2 leakage. Various aspects of these challenges are addressed by collaborative projects within Center for Frontiers in Subsurface Energy Security (CFSES). Challenge 1 – Sustaining large storage rates. To offset the annual CO 2 emissions of in the United States, ~7 billion metric tons of CO 2 must be injected into the storage reservoirs annually. Injected CO 2 forms a plume that starts spreading, displacing originally resident brine, though inefficiently so. Because of its low viscosity, and buoyant forces, a CO 2 plume rises to the reservoir rock-caprock interface. Injecting large volumes of scCO 2 at sufficiently high rates into subsurface storage formations leads to increases in pore pressures, potential expansion of the reservoir rock, and may result in fracturing of the reservoir rock and/or caprock. CFSES research uses existing and new experimental and modeling approaches to identify chemical-physical controls on the permeability and pore pressure dynamics, anticipating geomechanical (fracturing) events, predicting multi-phase flow patterns and trapping of CO 2 . Challenge 2 – Using pore space with unprecedented efficiency. Since large volumes of scCO 2 are to be stored, the volume available in storage reservoirs must be used efficiently. Storage efficiency is defined as a fraction of pore space occupied by carbon dioxide. Current estimates are that less than 5 percent of available pore volume is available for storage because scCO 2 , having a smaller density and viscosity than reservoir brine, tends to form viscous fingers, and bypass available pore space. This flow regime results in a CO 2 plume spreading over large areas in subsurface. The research goal in Challenge 2 is to advance the fundamental understanding of two-phase flow through porous media, including molecular-to meter- scale experimental and modeling approaches. This work leads to novel strategies to ensure that injected CO 2 occupies more than 5% of the pore space, ideally up to 50%. Challenge 3 – Controlling undesired or unexpected behavior. Following the injection of scCO 2 , the subsurface reservoir re-equilibrates to different physical and chemical states. This re-equilibration in space and time could lead to unexpected and/or undesired behavior: fracturing of reservoir rock and/or caprock, development of preferential flow paths, CO 2 leakage (to the surface or overlaying fresh water reservoirs), induced seismicity, and activation of faults. One of the main research goals of CFSES was to advance the fundamental understanding of how individual chemical and physical processes are coupled. We particularly focused on the chemical-mechanical coupling, and flow-mechanical coupling. We collected experimental and modeling data to determine the temporal and spatial scales of the coupled processes, which may lead to pore collapse caused by creep, activation of fractures and faults, chemically-induced fracture propagation, and self-focusing of scCO 2 flow.

54 ENVIRONMENTAL SCIENCES↗

Resilient Distributed Frequency Regulation of Renewable Generators under Communication Interruptions

Modern power systems (MPSs) face significant challenges due to the high penetration of renewable energy sources (RESs) and new types of loads such as electric vehicles (EVs). Traditional load frequency control (LFC) methods struggle with the intermittent, stochastic nature of RESs, the near-zero inertia of power-electronics-based generators, and the mobility of controllable loads and battery systems. This paper introduces a novel resilient distributed frequency regulation method to address these issues. The proposed method employs a state space model to represent the dynamic behavior of participating power sources while accounting for stochastic switching processes to model structural and parameter variations caused by disruptions such as generator connection/disconnection, communication interruptions, and physical faults. By integrating these dynamic and stochastic components, the method treats power grids as a comprehensive stochastic hybrid system. Our method enhances conventional frequency control by incorporating local stability control, neighborhood control decoupling, and coordination feedback. Theoretical analyses establish the stability, convergence, and resilience of the proposed method, and its effectiveness is validated through case studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

More Than 40 yr of Potentially Induced Seismicity Close to the San Andreas Fault in San Ardo, Central California

Evidence for fluid–injection–induced seismicity is rare in California hydrocarbon basins, despite widespread injection close to seismically active faults. We investigate a potential case of injection–induced earthquakes associated with San Ardo oilfield operations that began in the early 1950s. The largest potentially induced events occurred in 1955 (M L 5.2) and 1985 (M w 4.5) within ~6 km from the oilfield. We analyze Synthetic Aperture Radar interferometric images acquired by Sentinel–1A/B satellites between 2016 and 2020 and find surface deformation of up to 1.5 cm/yr, indicating pressure–imbalance in parts of the oilfield. Fluid injection in San Ardo is concentrated within highly permeable rocks directly above the granitic basement at a depth of ~800 m. Seismicity predominantly occurs along basement faults at 6–13 km depths. Seismicity and wastewater disposal wells are spatially correlated to the north of the oilfield. Temporal correlations are observed over more than 40 yr with correlation coefficients of up to 0.71 for seismicity within a 24 km distance from the oilfield. Such large distances have not previously been observed in California but are similar to the large spatial footprint of injection in Oklahoma. Furthermore, the San Ardo seismicity shows anomalous clustering with earthquakes consistently occurring at close spatial proximity but long interevent times. Similar clustering has previously been reported in California geothermal fields and may be indicative of seismicity driven by long–term, spatially persistent external forcing.

58 GEOSCIENCES↗

A flight expert system for on-board fault monitoring and diagnosis

An architecture for a flight expert system (FLES) to assist pilots in monitoring, diagnosing, and recovering from inflight faults is described. A prototype was implemented and an attempt was made to automate the knowledge acquisition process by employing a learning by being told methodology. The scope of acquired knowledge ranges from domain knowledge, including the information about objects and their relationships, to the procedural knowledge associated with the functionality of the mechanisms. AKAS (automatic knowledge acquisition system) is the constructed prototype for demonstration proof of concept, in which the expert directly interfaces with the knowledge acquisition system to ultimately construct the knowledge base for the particular application. The expert talks directly to the system using a natural language restricted only by the extent of the definitions in an analyzer dictionary, i.e., the interface understands a subset of concepts related to a given domain. In this case, the domain is the electrical system of the Boeing 737. Efforts were made to define and employ heuristics as well as algorithmic rules to conceptualize data produced by normal and faulty jet engine behavior examples. These rules were employed in developing the machine learning system (MLS). The input to MLS is examples which contain data of normal and faulty engine behavior and which are obtained from an engine simulation program. MLS first transforms the data into discrete selectors. Partial descriptions formed by those selectors are then generalized or specialized to generate concept descriptions about faults. The concepts are represented in the form of characteristic and discriminant descriptions, which are stored in the knowledge base and are employed to diagnose faults. MLS was successfully tested on jet engine examples.

Ali, Moonis↗

Temperature Dependent Cyclic Deformation Mechanisms in Haynes 188 Superalloy

The cyclic deformation behavior of a wrought cobalt-base superalloy, Haynes 188, has been investigated over a range of temperatures between 25 and 1000 C under isothermal and in-phase thermomechanical fatigue (TMF) conditions. Constant mechanical strain rates (epsilon-dot) of 10(exp -3)/s and 10(exp -4)/s were examined with a fully reversed strain range of 0.8%. Particular attention was given to the effects of dynamic strain aging (DSA) on the stress-strain response and low cycle fatigue life. A correlation between cyclic deformation behavior and microstructural substructure was made through detailed transmission electron microscopy. Although DSA was found to occur over a wide temperature range between approximately 300 and 750 C the microstructural characteristics and the deformation mechanisms responsible for DSA varied considerably and were dependent upon temperature. In general, the operation of DSA processes led to a maximum of the cyclic stress amplitude at 650 C and was accompanied by pronounced planar slip, relatively high dislocation density, and the generation of stacking faults. DSA was evidenced through a combination of phenomena, including serrated yielding, an inverse dependence of the maximum cyclic hardening with epsilon-dot, and an instantaneous inverse epsilon-dot sensitivity verified by specialized epsilon-dot -change tests. The TMF cyclic hardening behavior of the alloy appeared to be dictated by the substructural changes occuring at the maximum temperature in the TMF cycle.

Rao, K. Bhanu Sankara↗

Analysis of Potential Leakage Pathways and Mineralization within Caprocks for Geologic Storage of CO 2

We used a multifaceted approach to investigate the nature of caprocks above, and the interface between, reservoir-quality rocks that might serve as targets for carbon storage. Fieldwork in southeastern Utah examined the regional- to m-scale nature of faults and fractures across the sedimentiological interfaces. We also used microscopic analyses and mechanical modeling to examine the question as to how the contacts between units interact, and how fractures may allow fluids to move from reservoirs to caprock. Regional-­scale analyses using ASTER data enabled us to identify location of alteration, which led to site-­specific studies of deformation and fluid flow. In the Jurassic Carmel Formation, a seal for the Navajo Sandstone, we evaluated mesoscale variability in fracture density and morphology and variability in elastic moduli in the Jurassic Carmel Formation, a proposed seal to the underlying Navajo Sandstone for CO 2 geosequestration. By combining mechano-stratigraphic outcrop observations with elastic moduli derived from wireline log data, we characterize the variability in fracture pattern and morphology with the observed variability in rock strength within this heterolithic top seal. Outcrop inventories of discontinuities show fracture densities decrease as bed thickness increases and fracture propagation morphology across lithologic interfaces vary with changing interface type. Dynamic elastic moduli, calculated from wireline log data, show that Young’s modulus varies by up to 40 GPa across depositional interfaces, and by an average of 3 GPa across the reservoir/seal interface. We expect that the mesoscale changes in rock strength will affect the distributions of localized stress and thereby influence fracture propagation and fluid flow behavior within the seal. These data provide a means to closely tie outcrop observations to those derived from subsurface data and estimates of subsurface rock strength. We also studied damage zones associated normal faults in the Permian Cedar Mesa Sandstone, southeastern Utah. These faults are characterized by a single slip surfaces and damage zones containing deformation bands, veins, and joints. Field observations include crosscutting relationships, permeability increase, rock strength decrease, and ultraviolet light induced mineral fluorescence within the damage zone. These field observations combined with the interpreted paragenetic sequence from petrographic analysis, suggests a deformation history of reactivation and several mineralization events in an otherwise low-permeability fault. All deformation bands and veins fluoresce under ultraviolet light, suggesting connectivity and a shared mineralization history. Pre-­existing deformation features act as loci for younger deformation and mineralization events, this fault and its damage zone illustrate the importance of the fault damage zone to subsurface fluid flow. We model a simplified stress history in order to understand the importance of rock properties and magnitude of tectonic stress on the deformation features within the damage zone. The moderate confining pressures, possible variations in pore pressure, and the porous, fine-­grained nature of the Cedar Mesa Sandstone results in a fault damage zone characterized by enhanced permeability, subsurface fluid flow, and mineralization. Structural setting greatly influences fracture spacing and orientation. Three structural settings were examined and include fault proximity, a fold limb of constant dip, and a setting proximal to the syncline hinge. Fracture spacing and dominant fracture orientation vary at each setting and distinctions between regional and local paleo-stress directions can be made. Joints on the fold limb strike normal to the fold axis/bedding and are interpreted to be sub-parallel to the maximum regional paleo-stress direction as there is no fold related strain. Joints proximal to faults and the syncline hinge may have formed under local stress conditions associated with folding and faulting, and in some cases, are perpendicular to the maximum regional paleo-stress direction. Macroscale analyses of the Iron Wash fault, which cuts most of the stratigraphy of the reservoir- seal analogs, reveals that seal bypass occurs along faults with mixed lithologic composition. While portions of the fault may be effective seals, when modeled as a whole the fault zone cannot support a high CO 2 column. We adapted oil-field methods to calculate column heights and sealing capacities. Examination of the burial and tectonic histories of the rocks, coupled with field- and micro-­scale studies, allow us to examine the potential for seal failure using basic rock mechanics failure analyses. These studies reveal that the sealing lithologies experienced multiple episodes of deformation that resulted in numerous fractures and small faults. In a stress state based on burial history and overburden loads, we show that most of the seals could fail with normal to slightly excess pore pressures.

58 GEOSCIENCES↗

Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events, and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system. The artificial intelligence approach is useful because it provides (1) the use of human experts' knowledge of sensor behavior and faulty engine conditions in interpreting data; (2) the use of engine design knowledge and physical sensor locations in establishing relationships among the events of multiple sensors; (3) the use of stored analysis of past data of faulty engine conditions; and (4) the use of knowledge-based reasoning in distinguishing sensor failure from actual faults. The neural network approach appears promising because neural nets (1) can be trained on extremely noisy data and produce classifications which are more robust under noisy conditions than other classification techniques; (2) avoid the necessity of noise removal by digital filtering and therefore avoid the need to make assumptions about frequency bands or other signal characteristics of anomalous behavior; (3) can, in effect, generate their own feature detectors based on the characteristics of the sensor data used in training; and (4) are inherently parallel and therefore are potentially implementable in special-purpose parallel hardware.

Ali, Moonis↗

Cognitive barriers during monitoring-based commissioning of buildings

Monitoring-based commissioning (MBCx) is a continuous building energy management process used to optimize energy performance in buildings. Although monitoring-based commissioning (MBCx) can reduce energy waste by up to 20%, many buildings still underperform due to issues such as unnoticed system faults and inefficient operational procedures. While there are technical barriers that impede the MBCx process, such as data quality, the focuses of this paper are the non-technical, behavioral and organizational, barriers that contribute to issues initiating and implementing MBCx. In particular, this paper discusses cognitive biases, which can lead to suboptimal outcomes in energy efficiency decisions, resulting in missed opportunities for energy savings. This paper provides evidence of cognitive biases in decisions during the MBCx process using qualitative data from over 40 public and private sector organizations. The results describe barriers resulting from cognitive biases, listed in descending order of occurrence, including: risk aversion, social norms, choice overload, status quo bias, information overload, professional bias, and temporal discounting. Building practitioners can use these results to better understand potential cognitive biases, in turn allowing them to establish best practices and make more informed decisions. Finally, researchers can use these results to empirically test specific decision interventions and facilitate more energy efficient decisions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A tutorial on the CARE III approach to reliability modeling

The CARE 3 reliability model for aircraft avionics and control systems is described by utilizing a number of examples which frequently use state-of-the-art mathematical modeling techniques as a basis for their exposition. Behavioral decomposition followed by aggregration were used in an attempt to deal with reliability models with a large number of states. A comprehensive set of models of the fault-handling processes in a typical fault-tolerant system was used. These models were semi-Markov in nature, thus removing the usual restrictions of exponential holding times within the coverage model. The aggregate model is a non-homogeneous Markov chain, thus allowing the times to failure to posses Weibull-like distributions. Because of the departures from traditional models, the solution method employed is that of Kolmogorov integral equations, which are evaluated numerically.

Trivedi, K. S.↗