Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “utility rate analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 523 records · Page 29

Streaming Large-Scale Microscopy Data to a Supercomputing Facility

Data management is a critical component of modern experimental workflows. As data generation rates increase, transferring data from acquisition servers to processing servers via conventional file-based methods is becoming increasingly impractical. The 4D Camera at the National Center for Electron Microscopy generates data at a nominal rate of 480 Gbit s -1 (87,000 frames s -1 ⁠), producing a 700 GB dataset in 15 s. To address the challenges associated with storing and processing such quantities of data, we developed a streaming workflow that utilizes a high-speed network to connect the 4D Camera’s data acquisition system to supercomputing nodes at the National Energy Research Scientific Computing Center, bypassing intermediate file storage entirely. In this work, we demonstrate the effectiveness of our streaming pipeline in a production setting through an hour-long experiment that generated over 10 TB of raw data, yielding high-quality datasets suitable for advanced analyses. Additionally, we compare the efficacy of this streaming workflow against the conventional file-transfer workflow by conducting a postmortem analysis on historical data from experiments performed by real users. Our findings show that the streaming workflow significantly improves data turnaround time, enables real-time decision-making, and minimizes the potential for human error by eliminating manual user interactions.

4D-STEM↗

GraphCH: A Deep Framework for Assessing Cyber-Human Aspects in Insider Threat Detection

Insider threat is one of the most damaging cyber attacks that could cause the loss of intellectual property and enterprise data security breaches. Action sequence data such as host logs are used to investigate such threats and develop anomaly-based AI detectors. However, insider threat actions are similar to legitimate user activities, causing AI detectors to fail and suffer from high false alarm rates. Therefore, user cyber activity logs are inadequate to fully unfold insider threats. In this study, we adopt human psychological principles of risk-taking and impulsiveness along with host data to assess the influence and usefulness of human behavioral aspects in insider threat detection. Here, we hypothesize that individuals' impulsive and risk-taking behavior correlates with cyberspace activities. To validate our hypothesis, we conducted an IRB-approved study recruiting 35 participants who work in a large U.S. university and collected their cyber and psychological data for 90 days. Host and human-behavioral data analysis and mapping indicate that impulsive and risk-taking users trigger more system errors causing (un)intentional insider threats and are susceptible to attackers' social engineering and cognitive hacking. Utilizing cyber-human aspects, we introduce a Cyber-Human Graph Neural Network (GNN) based framework GraphCH to identify abnormal user behaviors and detect insider threats.

97 MATHEMATICS AND COMPUTING↗

Domain Shift Analysis in Chest Radiographs Classification in a Veterans Healthcare Administration Population

This study aims to assess the impact of domain shift on chest X-ray classification accuracy and to analyze the influence of ground truth label quality and demographic factors such as age group, sex, and study year. We used a DenseNet121 model pre-trained MIMIC-CXR dataset for deep learning-based multi-label classification using ground truth labels from radiology reports extracted using the CheXpert and CheXbert Labeler. We compared the performance of the 14 chest X-ray labels on the MIMIC-CXR and Veterans Healthcare Administration chest X-ray dataset (VA-CXR). The validation of ground truth and the assessment of multi-label classification performance across various NLP extraction tools revealed that the VA-CXR dataset exhibited lower disagreement rates than the MIMIC-CXR datasets. Additionally, there were notable differences in AUC scores between models utilizing CheXpert and CheXbert. When evaluating multi-label classification performance across different datasets, minimal domain shift was observed in the unseen VA dataset, except for the label “Enlarged Cardiomediastinum.” The subgroup with the most significant variations in multi-label classification performance was study year. These findings underscore the importance of considering domain shift in chest X-ray classification tasks, paying particular attention to the temporality of the exam. Our study reveals the significant impact of domain shift and demographic factors on chest X-ray classification, emphasizing the need for improved transfer learning and robust model development. Addressing these challenges is crucial for advancing medical imaging research and improving patient care.

chest X-ray image classification↗

Enhancement of Uranium Ionization Efficiencies Using Zn-MOF-74 Derived Nanoporous Ion Emitters for Thermal Ionization Mass Spectrometry

The recent introduction of nano-porous ion emitters (nano-PIEs) formed from metal organic frameworks (MOFs) has demonstrated the potential to enhance sensitivity for thermal ionization mass spectrometry (TIMS). Nano-PIEs take advantage of the parent MOF’s chemical and structural tunability to form scaffolds for ion emitters. A study by Barpaga et al. 2023 on MOF-74 as the parent material found that with high volatility metals in their framework uranium sample utilization efficiency (SUE) increases by up to nine-fold (e.g., Zn-MOF-74) compared to that of the analyte on a bare filament (~0.05%). Here, in this study, we investigate the performance of Zn-MOF-74 to maximize uranium efficiencies at the trace level (= 10 -12 g) by altering the parent MOF morphology and chemistry (i.e., MOF crystal sizes and thermal degradation) and optimizing its integration with TIMS (i.e., MOF mass on a filament and ramp conditions). We observed improvement in SUE up to 20 times (≤1.0%) that of a bare filament load when nano-PIEs derived from nanocrystals of Zn-MOF-74 were heated under a specific current ramp condition. This demonstrates that rates of nano-PIE structural collapse during TIMS analysis and the subsequently formed nanomaterials (and their features) can be tuned to control analyte ionization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Methods—Kintsugi Imaging of Battery Electrodes: Distinguishing Pores from the Carbon Binder Domain using Pt Deposition

The mesostructure of porous electrodes used in lithium-ion batteries strongly influences cell performance. Accurate imaging of the distribution of phases in these electrodes would allow this relationship to be better understood through simulation. However, imaging the nanoscale features in these components is challenging. While scanning electron microscopy is able to achieve the required resolution, it has well established difficulties imaging porous media. This is because the flat imaging planes prepared using focused ion beam milling will intersect with the pores, which makes the images hard to interpret as the inside walls of the pores are observed. It is common to infiltrate porous media with resin prior to imaging to help resolve this issue, but both the nanoscale porosity and the chemical similarity of the resins to the battery materials undermine the utility of this approach for most electrodes. In this study, a technique is demonstrated which uses in situ infiltration of platinum to fill the pores and thus enhance their contrast during imaging. Reminiscent of the Japanese art of repairing cracked ceramics with precious metals, this technique is referred to as the kintsugi method. The images resulting from applying this technique to a conventional porous cathode are presented and then segmented using a multi-channel convolutional method. We show that while some cracks in active material particles were empty, others appear to be filled (perhaps with the carbon binder phase), which will have implications for the rate performance of the cell. Energy dispersive X-ray spectroscopy was used to validate the distribution of phases resulting from image analysis, which also suggested a graded distribution of the binder relative to the carbon additive. The equipment required to use the kintsugi method is commonly available in major research facilities and so we hope that this method will be rapidly adopted to improve the imaging of electrode materials and porous media in general.

25 ENERGY STORAGE↗

In Situ Characterization of Surface Recombination in p-Si/SiO x Based Photoelectrochemical Cells

Time-resolved infrared (TRIR) and electrochemical impedance spectroscopy (EIS) were utilized to quantify surface states present at silicon oxide (SiO x ) protected crystalline p-Si electrolyte interfaces. The primary goal was to identify p-Si/SiO x photoelectrodes with both low surface recombination rates and efficient multi-electron transfer to an acceptor present in the external electrolyte. Three SiO x layers were investigated: native oxide (nOx), chemical oxide (cOx), and rapid thermal annealed (RTA) thermal oxide (tOx). Comparative study with [Ru(bpy) 3 ](PF 6 ) 2 as the electron acceptor indicated that tOx was most optimal with a small effective recombination rate, multi-electron transfer capability, and photovoltage of 500 ± 50 mV. A secondary goal was to analyze the surface recombination rates with the Shockley–Read–Hall (SRH) kinetic model. Two surface states were identified from this analysis, one closer to the CB edge (V t,1 ) and the other near the midgap (V t,2 ). EIS and SRH analyses revealed that a forming gas (5% H 2 /N 2 ) anneal (FGA) decreased surface recombination for tOx and nOx through a lower density of surface states. In the case of tOx, the infrared data indicated that V t,2 was completely removed. Here, the energetic positions of the band edges were correlated with the surface state density; low densities corresponded to more favorable potentials for inversion layer formation, which is expected to be most optimal for photocatalysis. Collectively this study indicates that the free carrier dynamics provided by TRIR represent a powerful in situ probe of the band edge and the surface state energetics in silicon based photoelectrochemical cells.

Electrochemical Impedance Spectroscopy↗

Interpreting test temperature and loading rate effects on the fracture toughness of polymer-metal interfaces via time–temperature superposition

Here, in this letter, we present interfacial fracture toughness data for a polymer-metal interface where tests were conducted at various test temperatures T and loading rates $\dot{δ}$. An adhesively bonded asymmetric double cantilever beam (ADCB) specimen was utilized to measure toughness. ADCB specimens were created by bonding a thinner, upper adherend to a thicker, lower adherend (both 6061 T6 aluminum) using a thin layer of epoxy adhesive, such that the crack propagated along the interface between the thinner adherend and the epoxy layer. The specimens were tested at T from 25 to 65 °C and $\dot{δ}$ from 0.002 to 0.2 mm/s. The measured interfacial toughness Γ increased as both T and $\dot{δ}$ increased. For an ADCB specimen loaded at a constant $\dot{δ}$, the energy release rate G increases as the crack length a increases. For this reason, we defined rate effects in terms of the rate of change in the energy release rate $\dot{G}$. Although not rigorously correct, a formal application of time–temperature superposition (TTS) analysis to the Γ data provided useful insights on the observed dependencies. In the TTS-shifted data, Γ decreased and then increased for monotonically increasing $\dot{G}$. Thus, the TTS analysis suggests that there is a minimum value of Γ. This minimum value could be used to define a lower bound in Γ when designing critical engineering applications that are subjected to T and $\dot{δ}$ excursions.

36 MATERIALS SCIENCE↗

Dynamic optimization and economic evaluation of flexible heat integration in a hybrid concentrated solar power plant

Hybridization of concentrated solar power (CSP) plants provides flexibility in operation that can drastically improve the solar-to-electric (STE) efficiency and levelized cost of electricity (LCOE) relative to standalone CSP plants. Flexible heat integration (FHI) is a novel concept where the collection and integration of CSP within a power plant is modified relative to the amount of solar energy available. FHI improves the thermal efficiency of a hybrid solar tower steam Rankine cycle power plant but leads to increased pumping needs due to continuously elevated molten salt flow rates through the collection system, which can negatively impact STE efficiency. The present work is carried out to maximize the STE efficiency of a hybrid CSP plant utilizing FHI by employing a dynamic optimization framework where a genetic algorithm optimizes the operation of the plant over a given solar irradiance profile. The study concerns a plant hypothetically located in Salt Lake City, Utah. Here, the optimization results confirm the accuracy of a predictive heuristic where the preferred operation of the plant can be estimated relative to local peaks in the incident power generated by the heliostat collection field. The optimized FHI operation demonstrates a yearly STE efficiency of 13.8%, whereas the equivalent base-level hybrid and solar-only plants exhibit solar efficiencies of 13.4% and 11.2%, respectively. Economic analysis shows that FHI reduces yearly natural gas costs, leading to a $\$0.5$/MWh reduction in LCOE relative to the base-level hybrid configuration. Overall, the results show that hybrid FHI schemes exhibit economic benefits along with observed thermodynamic improvements.

14 SOLAR ENERGY↗

Roles of Mn and Co in Ni-rich layered oxide cathodes synthesized utilizing a Taylor Vortex Reactor

It is reported that layered oxides, composed of nickel, manganese, and cobalt (NMC), are sought after as cathode materials which provide improved energy density, cycle life, and safety in commercial lithium ion batteries (LIBs). Increasing Ni contents higher than 80% can provide even higher practical discharge capacities >200 mAh/g and similar to ~4 V discharge potential vs Li/Li + , making them promising cathodes for next generation LIBs. However, rapid capacity fade during cycling and heat-related safety concerns are delaying their successful transition to industry. We report systematic performance optimization of LiNiO 2 , LiNi 0.9 Mn 0.1 O 2 , and LiNi 0.9 Co 0.1 O 2 high Ni layered oxide cathodes synthesized by utilizing a Taylor Vortex Reactor. Co-free LiNi 0.9 Mn 0.1 O 2 cathode showed 200 mAh/g highest discharge capacity at 0.1 C rate with 84% retention after 103 cycles at 0.3C rate while LiNi 0.9 Co 0.1 O 2 cathode showed higher initial but poor cycle life (225 mAh/g highest discharge capacity at 0.1C rate with only 56% capacity retention after 103 cycles at 0.3 C rate. Synchrotron based X-ray diffraction (SXRD), X-ray absorption spectroscopy (XAS) and focused ion beam (FIB) imaging of pristine and cycled cathodes after 103 cycles provided important information on degradation mechanism. The roles of Mn and Co on layered structure formation, charge balance, cationic mixing, and electrochemical performance were elucidated using the crystallographic information from XRD refinement and electronic state analysis from XAS providing valuable information to design future Ni-rich layered oxide cathodes.

25 ENERGY STORAGE↗

CO 2 methanation reaction pathways over unpromoted and NaNO 3 -promoted Ru/Al 2 O 3 catalysts

Catalytic CO 2 sorbents, materials that adsorb and pre-concentrate CO 2 on the catalyst surface prior to subsequent conversion, are becoming important materials in CO 2 capture and utilization. In this work, a prototypical CO 2 methanation catalyst – Ru/Al 2 O 3 – and a related catalytic sorbent – NaNO 3 /Ru/Al 2 O 3 – are used for CO 2 methanation in flowing hydrogen in a fixed bed reactor at temperatures ranging from 220 to 280 °C. Activation energies for the NaNO 3 /Ru/Al 2 O 3 material are slightly higher than unpromoted Ru/Al 2 O 3 catalysts, and the reaction orders vary more significantly. In situ IR spectroscopy and steady-state isotopic kinetic analysis (SSITKA) using in situ IR/MS spectroscopy show that bicarbonate and linear carbonyl species are the likely reaction intermediates over unpromoted Ru/Al 2 O 3 , while bidentate carbonate, formate and linear carbonyl species are among likely reaction intermediates over NaNO 3 /Ru/Al 2 O 3 . Rate laws consistent with the obtained experimental data are proposed after kinetic modeling of multiple plausible reaction pathways. In conclusion, results suggest that the pathway over the NaNO 3 /Ru/Al 2 O 3 catalyst likely has an additional kinetically relevant irreversible step in the CO 2 methanation reaction pathway.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Numerical Optimization of Spray-Guided Spark Assistance for Cold Idle Operation in a Heavy-Duty Gasoline Compression Ignition Engine

This article describes the results of a response surface model (RSM)-based numerical optimization campaign for spray-guided spark assistance at cold operations in a heavy-duty gasoline compression ignition (GCI) engine. On the basis of an earlier work on spark-assisted GCI cold combustion, a space-filling design of experiments (DoE) method was first undertaken to investigate a multitude of hardware design variables and engine operating parameters. The main design variables included the number of injector nozzles, fuel split quantities and injection timings, and spark timing. The objective variables were engine combustion efficiency (ŋ c ), maximum pressure rise rate (MPRR), and engine-out nitrogen oxide (NO x ) emissions. A total of 150 design candidates were automatically generated using the Sobol sequence method provided by the commercial software package, CAESES. Then, closed-cycle computational fluid dynamic (CFD) spark-assisted GCI simulations under cold idling operations were performed. The outcomes from the CFD-DoE design campaign were utilized to construct high-fidelity RSMs that allowed for further design optimization of the spark plug- and fuel injector-related design variables, along with fuel injection strategy parameters. A merit function with respect to objective variables was formulated with an appropriate weight assignment on each objective variable. Finally, the best design candidate was identified from the RSM-based optimization process and further validated in the CFD analysis. The best design candidate showed the potential to significantly improve combustion efficiency (ŋ c > 90%) over the baseline at cold idle while satisfying MPRR and NOx emissions constraints (MPRR < 5 bar/CAD and NO x < 4.5 g/kWh).

33 ADVANCED PROPULSION SYSTEMS↗

Evaluating the Effectiveness of Soil Profile Rehabilitation for Pluvial Flood Mitigation Through Two-Dimensional Hydrodynamic Modeling

Pluvial flooding, driven by increasingly impervious surfaces and intense storm events, presents a growing challenge for urban areas worldwide. In Baltimore City, MD, USA, climate change, rapid urbanization, and aging stormwater infrastructure are exacerbating flooding impacts, resulting in significant socio-economic consequences. This study evaluated the effectiveness of a soil profile rehabilitation scenario using a 2D hydrodynamic modeling approach for the Tiffany Run watershed, Baltimore City. This study utilized different extreme storm events, a high-resolution (1 m) LiDAR Digital Terrain Model (DTM), building footprints, and hydrological soil data. These datasets were integrated into a fully coupled 2D hydrodynamic model, the City Catchment Analysis Tool (CityCAT), to simulate urban flood dynamics. The pre-soil rehabilitation simulation revealed a maximum water depth of 3.00 m in most areas, with hydrologic soil groups C and D, especially downstream of the study area. The post-soil rehabilitation simulation was targeted at vacant lots and public parcels, accounting for 33.20% of the total area of the watershed. This resulted in a reduced water depth of 2.50 m. Additionally, the baseline runoff coefficient of 0.49 decreased to 0.47 following the rehabilitation, and the model consistently recorded a peak runoff reduction rate of 4.10 across varying rainfall intensities. The validation using a contingency matrix demonstrated true-positive rates of 0.75, 0.50, 0.64, and 0 for the selected events, confirming the model’s capability at capturing real-world flood occurrences.

Baltimore City↗

Discovery and adaptation of microbes that degrade oxidized low-density polyethylene films

There is a growing interest in developing a methodology for effectively cleaving carbon–carbon (C–C) bonds in polymer backbones through bioconversion processes that utilize microorganisms and their enzymes. This upsurge of interest is driven by the goal of achieving a circular economy. Polyolefin post-consumer plastics are a substantial source of carbon, but the recycling potential is severely limited. Upcycling routes are needed for converting polyolefin post-consumer plastics into value-added products while concurrently mitigating adverse environmental effects. These materials contain carbon-based chemicals that can, in principle, serve as the feedstock for microbial metabolism. Some microbes have been reported to grow on polyolefin plastics, but the rate of biodegradation is insufficient for industrial processes. In this study, low-density polyethylene (LDPE) films were subjected to two mild ozone-based oxidation treatments, which facilitated biodegradation. The degree of oxidation was determined by Fourier transform infrared spectroscopy via analysis of the carbonyl index (1,710/1,460 cm −1 ), which ranged from 0.3 to 2.0, and also via analysis of the carboxylic acid content. Following oxidation of the films, studies were conducted to investigate the ability of a panel of polyvinyl alcohol-degrading microbes to degrade the oxidized films. A defined minimal medium was used to cultivate and assess microbial growth on the oxidized films. Following 45 days of cultivation, the most effective strains were further cultivated up to three additional generations on the oxidized film substrates to improve their ability to degrade the oxidized LDPE films. After these enrichments, we identified a strain from the third generation of Pseudomonas sp. Rh926 that exhibited significant cell growth and reduced the oxidized LDPE film mass by 25% in 30 days, demonstrating an enhanced capacity for degrading the oxidized LDPE films.

Adaptation↗

Electrocatalytic Oxidative Coupling of Methane on NiFe Exsolved Perovskite Anode: Effect of Water

Oxidative coupling of methane (OCM) can be performed electrocatalytically by utilizing solid oxide cells, which provide a readily controlled oxygen supply through dense electrolytes. La 0.7 Sr 0.2 Ni 0.2 Fe 0.8 O 3 (LSNF) perovskite is an effective anode for OCM. Its surface characteristics and electrocatalytic activity can be improved by reduction and the resultant exsolution of bimetallic NiFe nanoparticles from its bulk. X-ray diffraction (XRD) and environmental transmission electron microscopy proved that the evolution of hetero-phases under reducing environment resulted in bimetallic NiFe nanoparticles being formed on the surface. Further, a 36 % improvement in C 2+ hydrocarbon production rate was achieved due to the reduction of LSNF with the exsolved NiFe nanoparticles. Co-feeding of H 2 O enhanced selective conversion of CH 4 resulting in the production rate of C 2+ hydrocarbons being increased by 56 %. Analysis of impedance spectra and in-situ DRIFTS under a CH 4 +H 2 O atmosphere provided an understanding for the enhancement on the electrocatalytic OCM.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis and Characterization of Four-quadrant Switches based Commutation Cell

A four-quadrant switch (FQS) blocks either polarity voltage and controls current flow in both directions. Unlike voltage-source converters, in which two-quadrant switches operate over a narrow voltage range, four-quadrant switches are required to operate over a wide range of both voltage and current in applications such as matrix converters and current-source converters. Furthermore, matrix converters require multi-step commutation schemes compared to two-step schemes for current-bidirectional switch based voltage-source converters and voltage-bidirectional switch based current-source converters. This paper provides a generalized overview of commutation schemes used for two and four quadrant switches based two-level commutation cells, identifies comparison indices for FQS commutation schemes, and discusses the need for adaptive commutation-step times for wide voltage and current variation applications. Also, the static and dynamic characteristics of 1.2 kV rated FQS implementations utilizing commercial SiC MOSFETs from four different manufacturers and novel monolithic SiC BiDirectional Field Effect Transistor (BiDFET) have been reported.

Commutation cell, four quadrant switch, SiC Bidire↗

PV Degradation Modeling: Applying Geospatial Workflows with "PVDeg"

Accurate degradation modeling is essential for predicting photovoltaic (PV) module performance, estimating longevity and informing design decisions. With degradation rates varying significantly by location, geospatial analysis is critical for PV and broader applications, such as agrivoltaics, weathering and environmental data analysis. This work presents PVDeg, an open-source tool designed for geospatial degradation analysis. PVDeg integrates meteorological data from global sources, including the National Solar Radiation Database (NSRDB) and Photovoltaic Geographical Information System (PVGIS), with degradation models. The toolkit enables users to customize geospatial workflows by integrating weather data, material parameters, and user-defined Python functions. It facilitates accelerated downloads of NSRDB and PVGIS datasets and optimizes geospatial point selection to preserve data density in regions of interest. Additionally, PVDeg provides a local database for storage and spatial queries, supporting large-scale analyses without the need for high-performance computing (HPC) resources. PVDeg provides a foundational workflow that extends its utility beyond PV applications, enabling researchers to analyze geospatial processes across discipline.

14 SOLAR ENERGY↗

Material Selection and Sizing of a Thermoelectric Generator (TEG) for Power Generation in a Self-Powered Heating System

By employing the high temperature heat source to directly generate the electricity needed to power auxiliary systems in a natural gas furnace, boiler or hot water heater, a “self-powered” heating system can provide several benefits. Compared with a traditional furnace, boiler or hot water heater, when overall fuel utilization is kept constant, the self-powered system will have a higher primary energy efficiency, lower operating costs, and dramatically improved building safety and resilience during electric grid outages. Furthermore, a self-powered heating system only has a single utility connection – natural gas, without an electric connection – thus simplifying installation. A thermoelectric generator can be used for direct energy conversion of thermal energy to electricity with no moving parts, which offers a very simple means to provide power for the self-powered heating system, and the operation is without noise or vibration and can thus provide a very long system life. This paper provides an analysis focused on materials selection and the thermal power requirements for a thermoelectric generator (TEG) for use in a self-powered heating system. The dimensionless figure of merit for thermoelectric materials, zT, is used to estimate the optimal efficiency that can be achieved with a TEG to produce the electric power required in such an application. Comparisons of the predicted efficiency, the required heat transfer rate to the TEG and the heat transfer area needed for sustained operation under thermal conditions relevant to the self-powered heating application are made for several potential thermoelectric materials. This analysis was used to develop system requirements for a self-powered hot water heater using a TEG for electric power generation.

Laclair, Tim↗

Analysis of US Industrial Assessment Centers (IACs) implementation

Industrial energy assessments are a fundamental action toward developing a decarbonization strategy at any level. They provide an understanding of where energy efficiency opportunities exist and help to make informed business decisions about the costs and benefits of implementing sustainable policies and practices. This paper examines the effectiveness of the Department of Energy's Industrial Assessment Centers Program at providing useful energy-efficiency audits as well as the barriers faced by the program and plans for future growth and improvement. This paper presents an analysis of the program between 1981 and 2022, covering 20,290 industrial assessments and 151,198 recommendations, with $2.6 billion of recommended savings. The analysis includes a breakdown of the IAC recommendations and implemented projects based on both the industrial subsectors according to the Standard Industrial Classification code, energy type, and systems evaluated. The results include a 47 % implementation rate, a gap analysis to understand the missed opportunities, and a discussion about reasons for recommendation rejection. A comparison of the IAC Program with other country-level energy auditing or assessment programs was conducted, and suggestions for improving implementation rates were mentioned.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗