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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Implementation of McMurchie–Davidson Algorithm for Gaussian AO Integrals Suited for SIMD Processors

We report an implementation of the McMurchie− Davidson evaluation scheme for 1- and 2-particle Gaussian AO integrals designed for processors with Single Instruction Multiple Data (SIMD) instruction sets. Like in our recent MD implementation for graphical processing units (GPUs) [Asadchev, A.; Valeev, E. F.. J. Chem. Phys. 2024, 160, 244109.], variable-sized batches of shellsets of integrals are evaluated at a time. By optimizing for the floating point instruction throughput rather than minimizing the number of operations, this approach achieves up to 50% of the theoretical hardware peak FP64 performance for many common SIMD-equipped platforms (AVX2, AVX512, NEON), which translates to speedups of up to 30 over the state-of-the-art one-shellset-at-a-time implementation of Obara−Saika-type schemes in Libint for a variety of primitive and contracted integrals. As with our previous work, we rely on the standard C++ programming language such as the std::simd standard library feature to be included in the 2026 ISO C++ standard without any explicit code generation to keep the code base small and portable. The implementation is part of the open source LibintX library freely available at https://github.com/ValeevGroup/libintx.

Basis sets↗
DOE OSTI2019

Effects of interfacial ligand type on hybrid P3HT:CdSe quantum dot solar cell device parameters

In this work, a series of CdSe quantum dot acceptors possessing six different ligand frameworks (i.e., pivalic acid, pyridine, butylamine, tert-butylthiol, thiophenol, and tetrahydrothiophene) were used as platforms for investigating the influence of quantum dot surface chemistry on the performance of hybrid poly(3-hexythiophene-2,5-diyl) (P3HT):CdSe quantum dot bulk heterojunction (BHJ) solar cells. We confirm that the device parameters used to evaluate solar cell performance are significantly influenced by the nature of the quantum dot surface ligand. The dependence of short circuit current density ($J_{SC}$) on the CdSe ligand type was probed using ultrafast time-resolved photoluminescence (PL) measurements, and good correlations between the ligand-dependent trends in $J_{SC}$ and excited state lifetime were found, in which the P3HT:CdSe quantum dot BHJs with the shortest PL lifetimes possess the largest device current densities. The frontier energy levels of the quantum dot acceptors are significantly influenced by surface ligands, wherein the device open circuit potentials (VOC) were found to linearly correlate with the energy difference ($ΔE_{DA}$) between the HOMO of the P3HT donor and the electrochemically determined LUMO of the CdSe quantum dot acceptors over a range of 220 mV. This work demonstrates the versatility of quantum dot ligand engineering for tuning the device parameters and performance of hybrid solar cells.

14 SOLAR ENERGY↗
DOE OSTI2022

Transactional Knowledge Graph Generation To Model Adversarial Activities

A Knowledge Graph (KG) is a formal and structured representation of facts, relationships, and semantic descriptions of a set of entities. Traditionally, KGs are used to describe metadata about entities and to provide additional context to target application results. Many real-world domains also involve temporal interactions between entities in addition to the metadata data. Modeling these attributed transactions is a critical requirement when using KGs in complex real-world applications. Modeling adversarial activities is one such application that develops methodology and tools to produce realistic large-scale background activity graphs that include embedded Weapons of Mass Destruction (WMD) activity patterns. We present a novel platform for constructing a transactional knowledge graph from a diverse set of sources. We present the core components and architecture of the framework, and a use case for generating a background knowledge graph and WMD activity template to evaluate network alignment and subgraph matching algorithms.

Purohit, Sumit↗
DOE OSTI2024

Observation of millihertz-level cooperative Lamb shifts in an optical atomic clock

Collective couplings of atomic dipoles to a shared electromagnetic environment produce a wide range of many-body phenomena. We report on the direct observation of resonant electric dipole-dipole interactions in a cubic array of atoms in the many-excitation limit. The interactions produce spatially dependent cooperative Lamb shifts when spectroscopically interrogating the millihertz-wide optical clock transition in strontium-87. We show that the ensemble-averaged shifts can be suppressed below the level of evaluated systematic uncertainties for optical atomic clocks. Additionally, we demonstrate that excitation of the atomic dipoles near a Bragg angle can enhance these effects by nearly an order of magnitude compared with nonresonant geometries. Our work demonstrates a platform for precise studies of the quantum many-body physics of spins with long-range interactions mediated by propagating photons.

Science & Technology - Other Topics↗
DOE OSTI2026

HPC ODA Commons [SWR-26-003]

HPC ODA Commons is a community-driven platform for standardizing HPC operational data analytics. HPC sites generate enormous volumes of operational data - scheduler logs, accounting records, monitoring streams - but turning that data into actionable insight is needlessly hard. Each site builds bespoke parsers, schemas, and evaluation pipelines. Results can't be compared across institutions. Promising analytics ideas stay siloed because there's no shared language for describing the data, the experiments, or the outcomes. HPC ODA Commons fixes this by establishing community-governed contracts - versioned schemas, canonical artifacts, and benchmark recipes - that make ODA workflows discoverable, reproducible, and comparable. It pairs these standards with a practical, CLI-first toolkit that lets operators and researchers go from raw logs to standardized results without sending data off-cluster.

Menear, Kevin [National Laboratory of the Rockies ↗
DOE OSTI2017

FY2017 Final Report: Power of the People: A technical ethical and experimental examination of the use of crowdsourcing to support international nuclear safeguards verification.

Recent advances in information technology have led to an expansion of crowdsourcing activities that utilize the “power of the people” harnessed via online games, communities of interest, and other platforms to collect, analyze, verify, and provide technological solutions for challenges from a multitude of domains. To related this surge in popularity, the research team developed a taxonomy of crowdsourcing activities as they relate to international nuclear safeguards, evaluated the potential legal and ethical issues surrounding the use of crowdsourcing to support safeguards, and proposed experimental designs to test the capabilities and prospect for the use of crowdsourcing to support nuclear safeguards verification.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2016

SU-F-T-193: Evaluation of a GPU-Based Fast Monte Carlo Code for Proton Therapy Biological Optimization

Purpose: Biological treatment plan optimization is of great interest for proton therapy. It requires extensive Monte Carlo (MC) simulations to compute physical dose and biological quantities. Recently, a gPMC package was developed for rapid MC dose calculations on a GPU platform. This work investigated its suitability for proton therapy biological optimization in terms of accuracy and efficiency. Methods: We performed simulations of a proton pencil beam with energies of 75, 150 and 225 MeV in a homogeneous water phantom using gPMC and FLUKA. Physical dose and energy spectra for each ion type on the central beam axis were scored. Relative Biological Effectiveness (RBE) was calculated using repair-misrepair-fixation model. Microdosimetry calculations were performed using Monte Carlo Damage Simulation (MCDS). Results: Ranges computed by the two codes agreed within 1 mm. Physical dose difference was less than 2.5 % at the Bragg peak. RBE-weighted dose agreed within 5 % at the Bragg peak. Differences in microdosimetric quantities such as dose average lineal energy transfer and specific energy were < 10%. The simulation time per source particle with FLUKA was 0.0018 sec, while gPMC was ∼ 600 times faster. Conclusion: Physical dose computed by FLUKA and gPMC were in a good agreement. The RBE differences along the central axis were small, and RBE-weighted dose difference was found to be acceptable. The combined accuracy and efficiency makes gPMC suitable for proton therapy biological optimization.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2022

Using OSSEs to Evaluate the Impacts of Geostationary Infrared Sounders

An observing system simulation experiment (OSSE) was performed to assess the impact of assimilating hyperspectral infrared (IR) radiances from geostationary orbit on numerical weather prediction, with a focus on the proposed sounder on board the Geostationary Extended Observations (GeoXO) program’s central satellite. Infrared sounders on a geostationary platform would fill several gaps left by IR sounders on polar-orbiting satellites, and the increased temporal resolution would allow the observation of weather phenomena evolution. The framework for this OSSE was the Global Modeling and Assimilation Office (GMAO) OSSE system, which includes a full suite of meteorological observations. The experiment additionally assimilated four identical IR sounders from geostationary orbit to create a “ring” of vertical profiling observations. Based on the experimentation, assimilation of the IR sounders provided a beneficial impact on the analyzed mass and wind fields, particularly in the tropics, and produced an error reduction in the initial 24–48 h of the subsequent forecasts. Specific attention was paid to the impact of the GeoXO Sounder (GXS) over the contiguous United States (CONUS) as this is a region that is well-observed and as such difficult to improve. The forecast sensitivity to observation impact (FSOI) metric, computed across all four synoptic times over the CONUS, reveals that the GXS had the largest impact on the 24-h forecast error of the assimilated hyperspectral infrared satellite radiances as measured using a moist energy error norm. Based on this analysis, the proposed GXS has the potential to improve numerical weather prediction globally and over the CONUS.

OSSE↗
DOE OSTI2024

Developing multi-gene CRISPRa/i programs to accelerate DBTL cycles in ABF hosts engineered for chemical production

This project developed and implemented a modular CRISPR activation and interference (CRISPRa/i) platform to accelerate strain optimization and pathway development for industrially relevant microbial hosts. By integrating multiplexed transcriptional perturbation tools with data-driven Design–Build–Test–Learn (DBTL) workflows, the team achieved reductions in cycle time and enhanced production of industrial aromatics, particularly 4-aminocinnamic acid (4-ACA), in Pseudomonas putida. Key accomplishments included: ● Development of a robust, tunable CRISPRa/i system in P. putida that enabled efficient multi-target gene regulation via guide RNA (gRNA) programs ● Completion of two full DBTL cycles, guided by machine learning (ML) models trained on transcriptomic and performance data, reducing engineering time by over 30% ● Optimization of multi-gene regulatory programs to balance expression of host and pathway modules, improve 4-ACA titers, and resolve metabolic bottlenecks ● Demonstration of system portability through a limited proof-of-concept extension in Acinetobacter baylyi, underscoring the generalizability of the approach ● Evaluation of strain performance on lignocellulosic biomass-derived substrates, demonstrating the feasibility of converting renewable carbon into aromatic building blocks These results illustrate the feasibility of applying ML-guided CRISPRa/i perturbation strategies to accelerate strain development in complex microbial systems. The resulting tools and datasets contribute to DOE objectives by improving platform predictability, reducing development costs, and enabling broader access to sustainable, economically viable bioproduction technologies.

09 BIOMASS FUELS↗
DOE OSTI2026

Stereochemically‐Controlled Fluorinated Copolymers for Selectively Permeable Barrier Applications

Selective oxygen permeability coupled with low water vapor transmission is essential for biomedical and packaging applications requiring controlled oxygen flux under humid conditions. However, most high‐performance barrier polymers depend on perfluoroalkyl substances (PFAS), whose persistence and regulatory restrictions limit their long‐term applicability. We designed a series of stereocontrolled thiol‐yne‐based polyesters, including both fluorinated and non‐fluorinated variants, for selective oxygen permeability with considerable water barrier performance. Tailoring polymer crystallinity and morphology tuned both oxygen transport and mechanical properties. Fluorinated polymers demonstrated enhanced hydrophobicity and water resistance while maintaining oxygen diffusivity within a range relevant to oxygen‐sensing applications. Structure–property relationships were elucidated through small‐ and wide‐angle X‐ray scattering, revealing semi‐crystalline domains influenced by fluorine content and dithiol chain length. Barrier performance was rigorously evaluated via water vapor transmission rate and dynamic vapor sorption, showing reduced water uptake with increasing dithiol monomer length and crystallinity. In conclusion, this work introduces a PFAS‐free alternative to conventional barrier materials and establishes a tunable materials platform with potential relevance for biomedical devices and packaging systems requiring controlled oxygen permeability.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Mission possible: Unify HPC and Big Data stacks towards application-defined blobs at the storage layer

HPC and Big Data stacks are completely separated today. The storage layer offers opportunities for convergence, as the challenges associated with HPC and Big Data storage are similar: trading versatility for performance. This motivates a global move towards dropping file-based, POSIX-IO compliance systems. However, on HPC platforms this is made difficult by the centralized storage architecture using file-based storage. In this paper we advocate that the growing trend of equipping HPC compute nodes with local storage redistributes the cards by enabling object storage to be deployed alongside the application on the compute nodes. Furthermore, such integration of application and storage not only allows fine-grained configuration of the storage system, but also improves application portability across platforms. In addition, the single-user nature of such application-specific storage obviates the need for resource-consuming storage features like permissions or file hierarchies offered by traditional file systems. In this article we propose and evaluate Blobs (Binary Large Objects) as an alternative to distributed file systems. Finally, we factually demonstrate that it offers drop-in compatibility with a variety of existing applications while improving storage throughput by up to 28%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Pre- and post-treatment image-based dosimetry in 90 Y-microsphere radioembolization using the TOPAS Monte Carlo toolkit

Objective.To evaluate the pre-treatment and post-treatment imaging-based dosimetry of patients treated with 90Y-microspheres, including accurate estimations of dose to tumor, healthy liver and lung. To do so, the Monte Carlo (MC) TOPAS platform is in this work extended towards its utilization in radionuclide therapy. Approach. In this study, five patients treated at the Massachusetts General Hospital were selected for this study. All patients had data for both pre-treatment SPECT-CT imaging using 99mTc-MAA as a surrogate of the 90Y-microspheres treatment and SPECT-CT imaging immediately after the 90Y activity administration. Pre- and post-treatment doses were computed with TOPAS using the SPECT images to localize the source positions and the CT images to account for tissue inhomoegeneities. We compared our results with analytical calculations following the voxel-based MIRD scheme. Main results. TOPAS results largely agreed with the MIRD-based calculations in soft tissue regions: the average difference in mean dose to the liver was 0.14 Gy GBq -1 (2.6%). However, dose distributions in the lung differed considerably: absolute differences in mean doses to the lung ranged from 1.2 to 6.3 Gy GBq -1 and relative differences from 153% to 231%. We also found large differences in the intra-hepatic dose distributions between pre- and post-treatment imaging, but only limited differences in the pulmonary dose. Significance. Doses to lung were found to be higher using TOPAS with respect to analytical calculations which may significantly underestimate dose to the lung, suggesting the use of MC methods for 90Y dosimetry. According to our results, pre-treatment imaging may still be representative of dose to lung in these treatments.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

High Multiplicity Trigger for long-lived particles in CMS detector

Searches for long-lived particles (LLPs) at the CMS experiment often involve unconventional event topologies that are difficult to efficiently select using standard trigger strategies. To improve sensitivity to such signatures during LHC Run 3 operation, a dedicated High Multiplicity Trigger (HMT) has been developed and deployed in the CMS trigger system. The trigger targets events containing unusually large numbers of hits in the CMS cathode strip chamber (CSC) muon detectors, a characteristic signature of several LLP scenarios involving displaced decays in the muon system. The HMT implementation, trigger logic, rate dependence with pileup, and operational stability are described. Optimized hit multiplicity thresholds are used to maintain acceptable trigger rates under high-luminosity and high-pileup conditions while preserving high efficiency across a broad range of LLP lifetimes and kinematic regimes. The trigger performance is evaluated using both simulated event samples and proton-proton collision data collected during Run 3 of the LHC. The HMT substantially extends the CMS sensitivity to non-standard signatures associated with LLP decays and provides a flexible platform for future searches for physics beyond the Standard Model.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

BigData Express: Toward Schedulable, Predictable, and High-Performance Data Transfer

Big Data has emerged as a driving force for scientific discoveries. Large scientific instruments (e.g., colliders, and telescopes) generate exponentially increasing volumes of data. To enable scientific discovery, science data must be collected, indexed, archived, shared, and analyzed, typically in a widely distributed, highly collaborative manner. Data transfer is now an essential function for science discoveries, particularly within big data environments. Although significant improvements have been made in the area of bulk data transfer, the currently available data transfer tools and services can not successfully address the high-performance and time-constraint challenges of data transfer required by extreme-scale science applications for the following reasons: disjoint end-to-end data transfer loops, cross-interference between data transfers, and existing data transfer tools and services are oblivious to user requirements (deadline and QoS requirements). Fermilab has been working on the BigData Express project to address these problems. BigData Express seeks to provide a schedulable, predictable, and high-performance data transfer service for big data science. The BigData Express software is being deployed and evaluated at multiple research institutions, which include UMD, StarLight, FNAL, KISTI, KSTAR, SURFnet, Ciena, and other sites. Meanwhile, the BigData Express research team is collaborating with the StarLight International/National Communications Exchange Facility to deploy BigData Express at various research platforms, including Pacific Research Platform, National Research Platform, and Global Research Platform. It is envisioned that we are working toward building a high-performance data transfer federation for big data science.

Lu, Qiming↗
DOE OSTI2019

Advances in Multi-Physics Modeling for Parallel Finite Element Code Suite ACE3P

SLAC developed ACE3P code suite is a comprehensive set of parallel finite-element codes for multi-physics modeling of particle accelerators. Running on massively parallel computer platforms for high fidelity and high accuracy simulation, ACE3P enables rapid virtual prototyping of accelerator and RF component design, optimization and analysis. Furthermore, recent advances of ACE3P have been focused on the implementation of advanced numerical algorithms, enhancement of multi-physics capabilities, and improvement of code performance on state-of-the-art high performance computing (HPC) platforms for large-scale RF modeling in accelerator applications and beyond. In this paper, we will present a nonlinear electromagnetic (EM) eigensolver for damping calculation of resonant modes for cavities coupled with waveguides, the thermal solver for accurate evaluation of heat loads in superconducting RF (SRF) cavity power coupler, the elastic solver for investigation of SRF cavity cryomodule (CM) bowing due to thermal effect, the frequency domain mechanical solver for studying SRF cavity mechanical oscillation modes, the particle tracking code for dark current simulation in SRF CM using a hybrid MPI+OpenMP parallel programing model, the time domain solver for high fidelity modeling of EM wave propagation for medical device in human body.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

SU-F-T-549: Validation of a Method for in Vivo 3D Dose Reconstruction for SBRT Using a New Transmission Detector

Purpose: Recently, there has been increased clinical use of stereotactic body radiation therapy (SBRT). SBRT treatments will strongly benefit from in vivo patient dose verification, as any errors in delivery can be more detrimental to the radiobiology of the patient as compared to conventional therapy. In vivo dose measurements, a commercially available quality assurance platform which is able to correlate the delivered dose to the patient’s anatomy and take into account tissue inhomogeneity, is the COMPASS system (IBA Dosimetry, Germany) using a new transmission detector (Dolphin, IBA Dosimetry). In this work, we evaluate a method for in vivo 3D dose reconstruction for SBRT using a new transmission detector, which was developed for in vivo dose verification for intensity-modulated radiation therapy (IMRT). Methods: We evaluated the accuracy of measurement for SBRT using simple small fields (2×2−10×10 cm2), a multileaf collimator (MLC) test pattern, and clinical cases. The dose distributions from the COMPASS were compared with those of EDR2 films (Kodak, USA) and the Monte Carlo simulations (MC). For clinical cases, we compared MC using dose-volume-histograms (DVHs) and dose profiles. Results: The dose profiles from the COMPASS for small fields and the complicated MLC test pattern agreed with those of EDR2 films, and MC within 3%. This showed the COMPASS with Dolphin system showed good spatial resolution and can measure small fields which are required for SBRT. Those results also suggest that COMPASS with Dolphin is able to detect MLC leaf position errors for SBRT. In clinical cases, the COMPASS with Dolphin agreed well with MC. The Dolphin detector, which consists of ionization chambers, provided stable measurement. Conclusion: COMPASS with Dolphin detector showed a useful in vivo 3D dose reconstruction for SBRT. The accuracy of the results indicates that this approach is suitable for clinical implementation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Additive Manufacturing of Parts and Tooling in Robotic Systems

ORNL worked with Transcend Robotics, LLC to explore additive manufacturing of the two-piece compression body for their ARTI mobile robot platform. Extrusion compression molding was identified as an effective means of manufacturing these parts. ORNL consulted on modifications to the housing design to accommodate the selected manufacturing process. Parts were printed using ORNL's FDM machines for testing and evaluation of the design as a precursor to molding the parts. The assembly and evaluation of the parts proved favorable and minor design changes to improve assembly and performance were identified.The goal is to develop a light weight and rugged two-part robotic enclosure for an unmanned ground vehicle UGV) that will be used in search and rescue applications. The FDM parts fabricated by ORNL allowed Transcend Robotics to assemble a prototype robot and verify that the new parts will meet the performance requirements. ORNL fabricated enclosure parts out of ABS and Nylon 12 materials such that the design could be tested prior to fabricating tooling for compression molding of Nylon 6 with carbon fiber fill. The robot was performance tested and compared with the previous manufacturing techniques and found to have superior performance.

42 ENGINEERING↗
DOE OSTI2018

Voltron Compatible Whole Building Root-Fault Detection and Diagnosis

Buildings consume more than 40% of primary energy in the U.S. Malfunctioning sensors, components, and control systems, as well as degrading components in Heating, Ventilating and Air-conditioning (HVAC) and lighting systems are main reasons for energy waste and unsatisfactory indoor environment. Field studies have shown that an energy saving of 5-30% of total building energy consumption and improved indoor air quality can be achieved by simply applying automated fault detection and diagnosis (AFDD), followed by corrections even if these are not done in real time. Extensive research has been made on the development of component level AFDD tools in the past two decades. However, in recent years, the development of method for a whole building level AFDD has received much attention. Here, a whole building fault refers to a fault happening in one subsystem but impact on more than one subsystems, or has a significant impact on building performances, such as building’s energy consumption. Existing component level AFDD tools could fail to detect or give false alarm for faults that trigger abnormalities in multiple subsystems. Isolating such whole building faults, which have impacts on multiple subsystems, is also challenging by simply using component based AFDD solutions. On the other hand, it might be more cost-effective for medium- or small-sized commercial buildings that have subsystems (e.g. primary cooling subsystem, air loop subsystem, heating subsystem, lighting subsystem, etc.) to install one whole building level AFDD tool, rather than many component level AFDD tools, to focus on significant faults. The focus of this project is firstly to provide training opportunities in building AFDD research area for undergraduate students and to develop a workforce pipeline in building sciences. The objective of the proposed research activities is to develop cost-effective and scalable AFDD solutions for whole building level faults. The developed AFDD solution is VOLTTRONTM compatible to further increase its plug-n-play capacity and the market penetration. VOLTTRONTM is an open-source innovative distributed control and sensing software platform developed by the Pacific Northwest National Laboratory. A VOLTTRONTM compatible AFDD tool brings the benefits such as low-cost deployment, and better building to grid integration, etc. The performance of the developed whole building AFDD tools is evaluated using data collected from a mixed-use medium-sized university campus building. Another significant goal of this project is to engage undergraduate students in research activities and expose them to building control and AFDD fields. A demonstration building – Nesbitt Hall at Drexel University is identified for this study. This demonstration building has a typical HVAC system configuration, which includes a water-cooled chiller system, three variable air volume (VAV) air handling unit (AHU) systems, and a hydronic heating system. Faults, that are expected to have a whole building level impact, are artificially implemented in this demonstration building for three different seasons. Building data have been collected in this project, which include fault free building automation system (BAS) data and BAS data that contain system behaviors caused by artificially implemented and naturally occurred faults. These collected data are used to evaluate the developed whole building AFDD tools. A data-driven method, which includes a weather and schedule-based pattern matching (WPM) method and Feature based Principal Component Analysis (FPCA) method, is developed for whole building level fault detection. Parameter sensitivity tests, including snapshot window size, data sample searching pool size, etc., are implemented to evaluate the impacts of various WPM-FPCA parameters. A data-driven and expert knowledge/rule-based method using Bayesian Network (BN) and WPM is developed for whole building level fault diagnosis. The developed WPM-BN method, which includes a two-layer BN structure model and BN parameters, are either learned from baseline data or developed from expert knowledge. The developed whole building AFDD tools are evaluated using BAS data collected from the demonstration building. Using the evaluation data set, the WPM-FPCA fault detection method is evaluated under two different Principle Component (PC) retention rates, i.e., 0.65 retention rate and 0.95 retention rate. It is observed that when using 0.65 PC retention rate, the WPM-FPCA fault detection method achieves a 79% fault detection rate (this rate reaches to 85% when including the six make-up fault test cases discussed in the next bullet), while when using 0.95 PC retention rate, the WPM-FPCA fault detection method achieves 100% fault detection rate (this rate remains to be 100% when including the six make-up fault test cases). Under both PC retention rates, the WPM-FPCA fault detection method demonstrates 0% false alarm rates. Using the evaluation data set, the developed WPM-BN fault diagnosis method has successfully diagnosed thirteen (13) faults out of the fourteen (14) fault test cases. The one mis-diagnosed case exhibits fewer fault symptoms in different subsystems, when compared with other fault test cases. Overall speaking, the developed whole building AFDD solutions demonstrate satisfactory fault detection/diagnosis accuracy with very low false alarm rate. Lastly, a survey and market study has been performed to understand the existing AFDD market, including its gaps and needs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗