A comparative ToF-SIMS and GC–MS analysis of phototrophic communities collected from an alkaline silica-depositing hot spring
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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Characterization of shale using Helium and Argon at high pressures
In order to estimate the shale gas in place and the eventual recovery during shale gas operations, one of the key requirements is to accurately characterize the shale’s petrophysical and transport properties such as porosity, permeability, diffusivity, and storage capacity. Despite the many efforts reported in the technical literature aiming to provide an improved understanding of the complex pore structures and the associated fluid flow in gas shales, complete characterization of organic-rich shale samples still poses a big challenge. Here, we have characterized mass transfer and sorption in shale at different length scales using Helium (He) and Argon (Ar) as probe gases. Thermogravimetric analysis (TGA) with a shale cube of ~1 cm 3 in size and gas expansion experiments with a full-diameter core (3.5” in diameter) were used to measure sorption kinetics/isotherms and mass transfer, respectively. Both samples are from the same depth/location in the Marcellus shale formation. The TGA steady-state technique was initially used to generate excess sorption isotherms for Ar, while dynamic TGA experiments were used to study its sorption kinetics. The TGA experiments demonstrate that Ar, which has a similar sorption potential as Methane, but is generally assumed to be inert, adsorbs onto the surfaces of the mesoporous and microporous regions of the shale samples according to a Langmuir-type behavior. Helium expansion experiments, on the full-diameter core, were used to measure the overall porosity, on the basis that He is a non-sorbing and inert gas as compared to Ar. The He expansion experiments, furthermore, allow us to delineate the mass transfer of gas across the inherent hierarchy of pore sizes, including macropores (macro- and microcracks), mesopores and micropores. Similar expansion experiments were also performed with Ar to study the combined impact of mass transfer and sorption. A triple-porosity model (TPM) was utilized to interpret the He expansion experiments with the shale core and to extract (estimate) relevant transport parameters. We report and compare here the diffusivities and permeabilities of the whole core for both He and Ar, as calculated from the modeling and fitting of the experimental data. On the premise that the shale cube is representative of the matrix region of the core, the Ar sorption kinetics from the cube experiments were subsequently combined with the transport parameters extracted from the He experiments to predict the behavior of the Ar expansion test with the full-diameter core. An excellent agreement is observed between the model predictions and the experimental data. The experimental observations and their interpretation indicate that one must be cautious when using Ar to estimate the true porosity and permeability of shales. In addition, we demonstrate that He and Ar probe gases, when used in tandem, can be employed effectively as a tool to characterize shales in terms of mass transfer and sorption dynamics across scales.
04 OIL SHALES AND TAR SANDS↗
Latent-space time evolution of non-intrusive reduced-order models using Gaussian process emulation
Non-intrusive reduced-order models (ROMs) have recently generated considerable interest for constructing computationally efficient counterparts of nonlinear dynamical systems emerging from various domain sciences. They provide a low-dimensional emulation framework for systems that may be intrinsically high-dimensional. This is accomplished by utilizing a construction algorithm that is purely data-driven. It is no surprise, therefore, that the algorithmic advances of machine learning have led to non-intrusive ROMs with greater accuracy and computational gains. However, in bypassing the utilization of an equation-based evolution, it is often seen that the interpretability of the ROM framework suffers. This becomes more problematic when black-box deep learning methods are used which are notorious for lacking robustness outside the physical regime of the observed data. In this article, we propose the use of a novel latent-space interpolation algorithm based on Gaussian process regression. Notably, this reduced-order evolution of the system is parameterized by control parameters to allow for interpolation in space. The use of this procedure also allows for a continuous interpretation of time which allows for temporal interpolation. The latter aspect provides information, with quantified uncertainty, about full-state evolution at a finer resolution than that utilized for training the ROMs. This research assesses the viability of this algorithm for an advection-dominated system given by the inviscid shallow water equations.
97 MATHEMATICS AND COMPUTING↗
Lagrangian geometrical optics of nonadiabatic vector waves and spin particles
Linear vector waves, both quantum and classical, experience polarization-driven bending of ray trajectories and polarization dynamics that can be interpreted as the precession of the "wave spin". Here, both phenomena are governed by an effective gauge Hamiltonian vanishing in leading-order geometrical optics. This gauge Hamiltonian can be recognized as a generalization of the Stern-Gerlach Hamiltonian that is commonly known for spin-1/2 quantum particles. The corresponding reduced Lagrangians for continuous nondissipative waves and their geometrical-optics rays are derived from the fundamental wave Lagrangian. The resulting Euler-Lagrange equations can describe simultaneous interactions of N resonant modes, where N is arbitrary, and lead to equations for the wave spin, which happens to be an (N 2 - 1)-dimensional spin vector. As a special case, classical equations for a Dirac particle (N = 2) are deduced formally, without introducing additional postulates or interpretations, from the Dirac quantum Lagrangian with the Pauli term. The model reproduces the Bargmann-Michel-Telegdi equations with added Stern-Gerlach force.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Search for gluino mediated bottom- and top-squark production in multijet final states in pp collisions at 8 TeV
A search for supersymmetry is presented based on events with large missing transverse energy, no isolated electron or muon, and at least three jets with one or more identified as a bottom-quark jet. A simultaneous examination is performed of the numbers of events in exclusive bins of the scalar sum of jet transverse momentum values, missing transverse energy, and bottom-quark jet multiplicity. The sample, corresponding to an integrated luminosity of 19.4 inverse femtobarns, consists of proton-proton collision data recorded at a center-of-mass energy of 8 TeV with the CMS detector at the LHC in 2012. The observed numbers of events are found to be consistent with the standard model expectation, which is evaluated with control samples in data. The results are interpreted in the context of two simplified supersymmetric scenarios in which gluino pair production is followed by the decay of each gluino to an undetected lightest supersymmetric particle and either a bottom or top quark-antiquark pair, characteristic of gluino mediated bottom- or top-squark production. Using the production cross section calculated to next-to-leading-order plus next-to-leading-logarithm accuracy, and in the limit of a massless lightest supersymmetric particle, we exclude gluinos with masses below 1170 GeV and 1020 GeV for the two scenarios, respectively.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Cosmic Overture Echoed in a Stellar Final Act: Implications of Nanohertz Gravitational Waves for Core Collapse Supernova Neutrinos
The growing evidence for nanohertz gravitational waves, from NANOGrav and other observations, may be pointing to a cosmological first-order phase transition at temperatures of 𝒪(10−100)MeV. Such an interpretation requires beyond the Standard Model dynamics in this energy range. If so, it may well be the case that galactic core-collapse supernova explosions would produce the key components related to the first-order phase transition, leaving detectable imprints on the spectrum of neutrinos emitted in the initial few seconds of the collapse. This might provide further evidence in support of the early universe interpretation of the nanohertz gravitational wave signal. The scenario proposed here is also suggestive of a low-mass seesaw mechanism to explain neutrino masses. We outline the prospects for future observations of Galactic supernovae to uncover the signals of this scenario, with further confirmation from future pulsar timing array measurements of primordial nanohertz gravitational waves.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Review of top quark mass measurements in CMS
The top quark mass is one of the most intriguing parameters of the standard model (SM). Its value indicates a Yukawa coupling close to unity, and the resulting strong ties to Higgs physics make the top quark mass a crucial ingredient for understanding essential aspects of the electroweak sector of the SM. This review offers the first comprehensive overview of the top quark mass measurements performed by the CMS Collaboration using the data collected at centre-of-mass energies of 7, 8, and 13 TeV. Moreover, a detailed description of the top quark event reconstruction is provided and dedicated studies of the dominant uncertainties in the modelling of the signal processes are discussed. The interpretation of the experimental results on the top quark mass in terms of the SM Lagrangian parameter is challenging and is a focus of an ongoing discussion in the theory community. The CMS Collaboration has performed two main types of top quark mass measurements, addressing this challenge from different perspectives: highly precise ‘direct’ measurements, based on reconstructed top quark decay products and relying exclusively on Monte-Carlo simulations, as well as ‘indirect’ measurements, where the simulations are employed to determine parton-level cross sections that are compared to fixed-order perturbative calculations. Recent mass extractions using Lorentz-boosted top quarks open a new avenue of measurements based on top quark decay products contained in a single particle jet, with promising prospects for accurate theoretical interpretations.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Transverse spin effects in hard semi-inclusive collisions
The nucleons (protons and neutrons) are by far the most abundant form of matter in our visible Universe; they are composite particles made of quarks and gluons, the fundamental quanta of Quantum Chromo Dynamics (QCD). The usual interpretation of the nucleon dynamics in high energy interactions is often limited to a simple one-dimensional picture of a fast moving nucleon as a collection of co-linearly moving quarks and gluons (partons), interacting accordingly to perturbative QCD rules. However, massive experimental evidence shows that, in particular when transverse spin dependent observables are involved, such a simple picture is not adequate. The intrinsic transverse motion of partons has to be taken into account; this opens the way to a new, truly 3-dimensional (3D) study of the nucleon structure. A review of the main experimental data, their interpretation and understanding in terms of new transverse momentum dependent partonic distributions, and the progress in building a 3D imaging of the nucleon is presented.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Probing the antagonistic effect of toluene as a component in surrogate fuel models at low temperatures and high pressures. A case study of toluene/dimethyl ether mixtures
There is a dearth of experimental data which examine the fundamental low-temperature ignition (T < 900 K) behavior of toluene resulting in a lack of data for the construction, validation, and interpretation of chemical kinetic models for commercial fuels. In order to gain a better understanding of its combustion chemistry, dimethyl ether (DME) has been used as a radical initiator to induce ignition in this highly knock resistant aromatic, and its influence on the combustion of toluene ignition was studied in both shock tube and rapid compression machines as a function of temperature (624–1459 K), pressure (20–40 atm), equivalence ratio (0.5–2.0), and blending ratio (100% toluene, 76% toluene (76T/24D), 58% toluene (58T/42D), 26% toluene (26T/74D) and 100% DME). We use several literature chemical kinetic models to interpret our experimental results. For mixtures containing high concentrations of toluene at low-temperatures none of these are capable of reproducing experiment. This then implies an incomplete understanding of the low-temperature oxidation pathways which control its ignition in our experimental reactors, and by extension, in spark- (SI) and compression-ignition (CI) engines, and an updated detailed chemical kinetic model is presented for engineering applications. Model analyses indicate that although the initial fate of the fuel is dominated by single-step H-atom abstraction reactions from both the benzylic and phenylic sites, the subsequent fate of the allylic and vinylic radicals formed is much more complex. Further experimental and theoretical endeavors are required to gain a holistic qualitative and quantitative chemical kinetics based understanding of the combustion of pure toluene, toluene blends, and commercial fuels containing other aromatic components, at temperatures of relevance to SI and CI engines.
30 DIRECT ENERGY CONVERSION↗
Investigation of Sampling-Probe Distorted Temperature Fields with X-Ray Fluorescence Spectroscopy
Flame-sampling experiments, especially in conjunction with laminar low-pressure premixed flames, are routinely used in combustion chemistry studies to unravel the identities and quantities of key intermediates and their pathways. In many instances, however, an unambiguous interpretation of the experimental and modeling results is hampered by the uncertainties about the probe-induced, perturbed temperature profile. To overcome this limitation, two-dimensional perturbations of the temperature field caused by sampling probes with different geometries have been investigated using synchrotron-based X-ray fluorescence spectroscopy. In these experiments, which were performed at the 7-BM beamline of the Advanced Photon Source (APS) at the Argonne National Laboratory, a continuous beam of hard X-rays at 15 keV was used to excite krypton atoms that were added in a concentration of 5 vol.-% to the unburnt gas mixture and the resulting krypton fluorescence at 12.65 keV was subsequently collected. The highly spatially resolved signal was converted into the local flame temperature to obtain temperature fields at various burner-probe separations as functions of the distance to the burner surface and the radial distance from the centerline. Multiple measurements were performed with different probe geometries and because of the observed impact on the temperature profiles the results clearly revealed the need to specify the sampling probe design to enable quantitative and meaningful comparisons of modeling results with flame-sampled mole fraction data. (C) 2018 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
Hansen, N.↗
Effects of dilution and pressure on combustion characteristics within externally heated micro-tubes
Here this study investigates the impact of pressure and dilution on combustion behavior of of C 2H6/air/N2 mixtures within an externally heated micro-tube using both experimental and analytical techniques. Experiments are conducted for pressures up to 10 bar at multiple dilution levels and document three flame regimes, i.e. weak flames, FREI and normal flames. Characteristic temperatures for flame stabilization, as well as and ignition and extinction are obtained by applying a novel thin filament pyrometry method (TFP), which uses a thin silicon carbide (SiC) filament that enables temperature measurements for both reacting and non-reacting cases. Results show a decrease of characteristic temperatures with increasing pressure, which can be which can be partially compensated by a decrease of O2 content. Further, regime transitions occur at lower velocity as the pressure increases, whereas weak flame positions are insensitive to dilution at a given pressure. Predictions from the analytical model compare favorably with experimental results. The most prominent finding is that as dilution increases, the transition from weak flame to FREI becomes less abrupt and is completely lost for high dilution levels (i.e. low O2 content). Both experimental and analytical results indicate that the unstable FREI combustion regime does not exist at high dilution levels, i.e. weak flame and normal flame regimes are no longer clearly separated. As FREI are interpreted as a cyclic transition from an ignition zone to a propagating flame, results for highly diluted conditions are interpreted as a combustion regime where classical flame propagation ceases to exist.
42 ENGINEERING↗
A comparison of computational models for predicting yield sooting index
Sooting propensity, a measurement of how much particulate matter is produced when a fuel is burned, is a property of significant interest among researchers who are striving to discover the next generation of cleaner, more efficient fuels and fuel additives. Many compounds are not viable as fuels and/or fuel additives, and as a result, designing cleaner-burning biofuels using only experimental techniques is inefficient. Predictive models have been instrumental in reducing this inherent difficulty, providing researchers with a tool to preemptively screen compounds before production and testing. The present work compares the accuracies and interpretabilities of existing models used to predict a particular measure of sooting propensity, Yield Sooting Index (YSI). These models include artificial neural networks, graph neural networks, and multivariate equations. A novel equation for predicting YSI based on atom path count and bond order is proposed, which can highlight key structural components that contribute to YSI. It was found that artificial neural networks slightly outperform graph neural networks and greatly outperform multivariate equations in blind (test set) prediction accuracy; however, graph neural networks and multivariate equations provide significantly more interpretability as to how compound structure relates to YSI. Predictions of YSI are compared to experimental measurements for previously un-tested compounds with cetane numbers comparable to diesel fuel (50-60) (butyl decanoate, ethyl decanoate, 1,4-bis(ethenoxymethyl)cyclohexane, and 5-heptyloxolan-2-one), and it was found that these compounds produce significantly less soot compared to diesel fuel.
09 BIOMASS FUELS↗
Late Holocene history of Tokotan Lake (Kuril Archipelago, Russian Far East): The use of lacustrine records for paleoclimatic reconstructions from geologically dynamic settings
A high-resolution, multiproxy analysis of a core from Tokotan Lake, Urup Island, illustrates the complex paleoenvironmental signals that can be preserved in sedimentary deposits from geologically active areas, such as the Kuril Archipelago. Diatom and geochemical analyses of the Tokotan core suggest a shallowing and lessening of the lake area over the last ~3450 cal BP. Without other proxies, the record could be interpreted as showing a general decrease in precipitation over the Late Holocene. However, palynological data indicate no change in vegetation, thereby implying no significant climatic variation. Neither of these paleoclimatic interpretations agrees with Late Holocene reconstructions from the Kuril Archipelago or the Russian mainland. Paleomagnetic data imply variable sediment sources during the lake's history, indicating alterations within the Tokotan catchment (e.g., shifts in gradients or sediment loads in the inflowing streams). Such changes would be particularly important in the Shabalina River, which today has formed a partial dam across the lake's outlet. Here, the results of the Tokotan study indicate that other factors (e.g., volcanism, seismic activity, sea-level changes) rather than climate were more probable determinants of the Late Holocene lake record. Given the geologic dynamism of the region, it is perhaps not surprising that paleo-records from the Kuril Islands display an inconsistency in the numbers and/or duration of proposed Holocene climatic oscillations, underscoring the importance of multiproxy investigations in areas that are or have been geologically dynamic.
58 GEOSCIENCES↗
Holocene paleoclimate history of Fallen Leaf Lake, CA., from geochemistry and sedimentology of well-dated sediment cores
Millennial-scale shifts in aridity patterns have been documented during the Holocene in the western United States, yet the precise timing, severity, and regional extent of these shifts prompts further study. Here we present lake sediment core data from Fallen Leaf Lake, a subalpine system at the southern end of the Lake Tahoe basin for which 80% of the contemporary inflow is derived from snowpack delivered by Pacific frontal storm systems. A high quality age model has been constructed using 14 C ages on plant macrofossils, 210 Pb, and the Tsoyowata tephra datum (7.74–7.95 cal kyr BP). One core captures the transition from the Late Tioga-younger Dryas glaciolacustrine package to laminated opaline clay at 11.48 cal kyr BP. Early Holocene sedimentation rates are relatively high (~1.9 mm/year) and cooler winter temperatures are inferred by the presence of pebbles interpreted to be transported out into the lake via shore ice. There is a geochemically distinct interval from ~4.71 to 3.65 cal kyr BP that is interpreted as a late Holocene neopluvial, characterized by depleted δ 13 C and lower C:N that point to reduced runoff of terrigenous organic matter, increased winter precipitation, and increased algal productivity. The largest Holocene signal in the cores occurs at the end of the neopluvial, at 3.65 cal kyr BP, and marks a shift into a climate state with variable precipitation, yet is overall more arid than the neopluvial. This new climate state persists for ~3 ka, until the Little Ice Age. Low sedimentation rates (0.5 mm/year), the homogeneous opaline sediment, and steadily increasing contributions of terrestrial vs. algal organic matter in these cores suggest that the lowstand state of Fallen Leaf Lake may have been the norm from 3.65 to 0.55 cal kyr BP, punctuated by short term high precipitation years or multi-year intervals capable of rapid short duration lake level rise. Fallen Leaf Lake is strongly influenced by changes in winter precipitation and temperature, manifested largely by the geochemical proxies, and highlights unique advantages of subalpine lakes in regional paleoclimate reconstructions.
58 GEOSCIENCES↗
Holocene paleoclimate change in the western US: The importance of chronology in discerning patterns and drivers
We report sediment in lakes and meadows forms a powerful archive that can be used to reconstruct environmental change through time. Reconstructions of lake level, of chemical, biological, and hydrological conditions, and of surrounding vegetation provide detailed information about past climate conditions, both locally and regionally. Indeed, most of our current knowledge of centennial- to millennial-scale climate variability in the arid western United States, where information about past hydroclimate is particularly important, comes from such sediment-based reconstructions. The pressing need for robust, precise predictions of future conditions is a significant motivation for paleoclimate science, and current research questions frequently require Holocene reconstructions to be resolved at sub-centennial timescales. Increasingly, regional syntheses seek to identify synoptic-scale patterns similar to those defined from modern observations (seasonal, interannual, multi-decadal, etc.) or to compare with the output of climate model simulations. However, the age control on existing records, especially those more than about 20 years old, is often sufficient only for millennial-scale interpretation. Here we assess the age control for 84 published and unpublished records from lakes and meadows in the Great Basin, California, and desert southwest, and use Bayesian modeling to evaluate the 95% uncertainty ranges for the 42 best-dated records. In the Late Holocene, about half of the 42 records have <400-year mean uncertainty ranges; however, high-precision age control is especially critical for young records, used to develop an accurate understanding of a proxy’s response to known climate variations. In the Middle Holocene, records vary from 400 to >800-year mean uncertainty and records of the Early Holocene have 600- to >1400-year mean uncertainty ranges. We find that the largest control on modeled uncertainties is dating density, with at least 2 dates/kyr being optimal and suggest obtaining “range-finder” dates at the onset of a study to better predict the total number of dates needed for an adequate age model. Such a density avoids a commonly observed phenomenon of significant peaks in uncertainty arising in gaps between age control points. Analysis of the uncertainties associated with proxy shifts reveal that more than half are >400 years. Although such large uncertainties currently prevent sub-centennial interpretations in most cases, increased dating density, strategic use of limited funds (including budgeting for a 2 date/kyr minimum at the proposal stage), construction of age-depth models with Bayesian methods, and critical evaluation of chronological uncertainty will shed light on past climate variability at finer timescales, enhancing our understanding of global and regional drivers of western U.S. climate.
54 ENVIRONMENTAL SCIENCES↗
A radiative transfer model for solar induced fluorescence using spectral invariants theory
Solar Induced chlorophyll Fluorescence (SIF) shows promise as an approach for estimating gross primary production (GPP) remotely. However, sun-target-sensor geometry and within-canopy absorption of SIF can alter the relationship between measured SIF and GPP, because sensors can only retrieve some unknown fraction of the total emitted SIF. Radiative transfer models that allow for variation in canopy structure and sensor angles are therefore needed to properly interpret SIF measurements. Spectral invariants allow decoupling of the wavelength-independent canopy structure and the wavelength-dependent leaf and soil spectrum in the radiative transfer process. Here we develop a simple analytical Fluorescence Radiative Transfer model based on Escape and Recollision probability (FluorRTER) to investigate the impact of canopy structure and sun-target-sensor geometry on SIF emissions. SIF simulations using the FluorRTER model agreed well the one-dimensional Soil-Canopy Observation of Photochemistry and Energy balance (SCOPE) model and the three-dimensional Fluorescence model with Weighted Photon Spread (FluorWPS) model. The fractional vegetation cover (FVC) and clumping effect have a large influence the SIF emission of 3D discontinuous canopies. For a moderate solar zenith angle (30°) and a clumped canopy (FVC?=?0.6), the difference between the directional observed SIF of a 3D discontinuous canopy and a 1D homogeneous canopy was as large as 43.2% and 38.4% for Photosystem I?+?II fluorescence at 685?nm and at 740?nm, respectively. By bridging the gap between observed SIF and total emitted SIF over 3D heterogeneous vegetation canopies, the FluorRTER model can assist with the angular normalization of SIF measurements and enable the more robust interpretation of how variations in SIF from directional and hemispherical in-situ, airborne and satellite observations relate to leaf and whole-canopy physiological processes.
Zeng, Yelu↗
Developing a common approach for classifying building stock energy models
Buildings contribute 40% of global greenhouse gas emissions; therefore, strategies that can substantially reduce emissions from the building stock are key components of broader efforts to mitigate climate change and achieve sustainable development goals. Models that represent the energy use of the building stock at scale under various scenarios of technology deployment have become essential tools for the development and assessment of such strategies. Within the past decade, the capabilities of building stock energy models have improved considerably, while model transferability and sharing has increased. Given these advancements, a new scheme for classifying building stock energy models is needed to facilitate communication of modeling approaches and the handling of important model dimensions. In this article, we present a new building stock energy model classification framework that leverages international modeling expertise from the participants of the International Energy Agency's Annex 70 on Building Energy Epidemiology. Drawing from existing classification studies, here we propose a multi-layer quadrant scheme that classifies modeling techniques by their design (top-down or bottom-up) and degree of transparency (black-box or white-box); hybrid techniques are also addressed. The quadrant scheme is unique from previous classification approaches in its non-hierarchical organization, coverage of and ability to incorporate emerging modeling techniques, and treatment of additional modeling dimensions. The new classification framework will be complemented by a reporting protocol and online registry of existing models as part of ongoing work in Annex 70 to increase the interpretability and utility of building stock energy models for energy policy making.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
A review of computing-based automated fault detection and diagnosis of heating, ventilation and air conditioning systems
We report faults in Heating, Ventilation, and Air Conditioning (HVAC) systems of buildings result in significant energy waste in building operation. With fast-growing sensing data availability and advancement in computing, computational modeling has demonstrated strong capability to detect and diagnose HVAC system faults, hence, ensuring efficient building operation. This paper comprehensively reviews the state-of-the-art computing-based fault detection and diagnosis (FDD) for HVAC systems. Overall, the reviewed computing-based FDD methods are classified as two major approaches: knowledge-based and data-driven approaches. We then identify multiple important topics, including data availability, training data size, data quality, approach generality, capability, interpretability, and required modeling efforts, along with corresponding metrics to summarize the most updated FDD development. Generally, the knowledge-based approaches are further divided as physics-based modeling, Diagnostic Bayesian Network, and performance indicator-based methods while data-driven approaches include supervised learning, unsupervised learning, and regression and statistics-based methods. State-of-the-art FDD development, remaining challenges, and future research directions are further discussed to push forward FDD in practice. Availability of fault data, capability of existing methods to deal with complex fault situations (such as simultaneous faults), modeling interpretability for data-driven methods, and required engineering efforts for physics-based methods are identified as remaining challenges in FDD development. Improving modeling fidelity and reducing modeling efforts are essential for applying physics-based methods in real buildings. Meanwhile, addressing fault data availability, increasing algorithm adaptability, and handling multiple faults are essential to further enhance the applicability of data-driven FDD approaches.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗