Search NASA⌕ Search

SEARCH · Search NASA

Results for “Perception”

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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Lignocellulosic Biomass-Derived Nanocellulose Crystals as Fillers in Membranes for Water and Wastewater Treatment: A Review

The improvement of membrane applications for wastewater treatment has been a focal point of research in recent times, with a wide variety of efforts being made to enhance the performance, integrity and environmental friendliness of the existing membrane materials. Cellulose nanocrystals (CNCs) are sustainable nanomaterials derived from microorganisms and plants with promising potential in wastewater treatment. Cellulose nanomaterials offer a satisfactory alternative to other environmentally harmful nanomaterials. However, only a few review articles on this important field are available in the open literature, especially in membrane applications for wastewater treatment. This review briefly highlights the circular economy of waste lignocellulosic biomass and the isolation of CNCs from waste lignocellulosic biomass for membrane applications. The surface chemical functionalization technique for the preparation of CNC-based materials with the desired functional groups and properties is outlined. Recent uses of CNC-based materials in membrane applications for wastewater treatment are presented. In addition, the assessment of the environmental impacts of CNCs, cellulose extraction, the production techniques of cellulose products, cellulose product utilization, and their end-of-life disposal are briefly discussed. Furthermore, the challenges and prospects for the development of CNC from waste biomass for application in wastewater treatment are discussed extensively. Finally, this review unraveled some important perceptions on the prospects of CNC-based materials, especially in membrane applications for the treatment of wastewater.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Preparation and Characterization of Inclusion Complexes of β-Cyclodextrin and Phenolics from Wheat Bran by Combination of Experimental and Computational Techniques

Bitterness often associated with whole wheat products may be related to phenolics in the bran. Cyclodextrins (CDs) are known to form inclusion complexes. The objective was to form inclusion complexes between β-CD and wheat phenolics. Pure phenolic acids (trans-ferulic acid (FA), caffeic acid (CA), and p-coumaric acid (CO)) and phenolic acids from wheat bran were used to investigate complex formation potential. Complexes were characterized by spectroscopy techniques, and a computational and molecular modeling study was carried out. The relative amount of complex formation between β-CD and wheat bran extract was CA > CO > FA. The phenolic compounds formed inclusion complexes with β-CDs by non-covalent bonds. The quantum-mechanical calculations supported the experimental results. The most stable complex was CO/β-CD complex. The ΔH value for CO/β-CD complex was -11.72 kcal/mol and was about 3 kcal/mol more stable than the other complexes. The QSPR model showed good correlation between binding energy and 1H NMR shift for the H5 signal. This research shows that phenolics and β-CD inclusion complexes could be utilized to improve the perception of whole meal food products since inclusion complexes have the potential to mask the bitter flavor and enhance the stability of the phenolics in wheat bran.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Optimization and Multimachine Learning Algorithms to Predict Nanometal Surface Area Transfer Parameters for Gold and Silver Nanoparticles

Interactions between gold metallic nanoparticles and molecular dyes have been well described by the nanometal surface energy transfer (NSET) mechanism. However, the expansion and testing of this model for nanoparticles of different metal composition is needed to develop a greater variety of nanosensors for medical and commercial applications. In this study, the NSET formula was slightly modified in the size-dependent dampening constant and skin depth terms to allow for modeling of different metals as well as testing the quenching effects created by variously sized gold, silver, copper, and platinum nanoparticles. Overall, the metal nanoparticles followed more closely the NSET prediction than for Förster resonance energy transfer, though scattering effects began to occur at 20 nm in the nanoparticle diameter. To further improve the NSET theoretical equation, an attempt was made to set a best-fit line of the NSET theoretical equation curve onto the Au and Ag data points. An exhaustive grid search optimizer was applied in the ranges for two variables, 0.1≤C≤2.0 and 0≤α≤4, representing the metal dampening constant and the orientation of donor to the metal surface, respectively. Three different grid searches, starting from coarse (entire range) to finer (narrower range), resulted in more than one million total calculations with values C=2.0 and α=0.0736. The results improved the calculation, but further analysis needed to be conducted in order to find any additional missing physics. With that motivation, two artificial intelligence/machine learning (AI/ML) algorithms, multilayer perception and least absolute shrinkage and selection operator regression, gave a correlation coefficient, R2, greater than 0.97, indicating that the small dataset was not overfitting and was method-independent. This analysis indicates that an investigation is warranted to focus on deeper physics informed machine learning for the NSET equations.

Demers, Steven M. E. (ORCID:0000000192213246)↗
DOE OSTI2025

Plant Defense Proteins: Recent Discoveries and Applications

Proteins play pivotal roles in safeguarding plants against numerous biotic and abiotic stresses. Understanding their biological functions and mechanisms of action is essential for advancing plant biology, agriculture, and biotechnology. This review considers the diversity and potential applications of plant defense proteins including pathogenesis-related (PR) proteins, chitinases, glucanases, protease inhibitors, lectins, and antimicrobial peptides. Recent advances, such as the omics technologies, have enabled the discovery of new plant defense proteins and regulatory networks that govern plant defense responses and unveiled numerous roles of plant defense proteins in stress perception, signal transduction, and immune priming. The molecular affinities and enzymatic activities of plant defense proteins are essential for their defense functions. Applications of plant defense proteins span agriculture, biotechnology, and medicine, including the development of resistant crop varieties, bio-based products, biopharmaceuticals, and functional foods. Future research directions include elucidating the structural bases of defense protein functions, exploring protein interactions with ligands and other proteins, and engineering defense proteins for enhanced efficacy. Overall, this review illuminates the significance of plant defense proteins against biotic stresses in plant biology and biotechnology, emphasizing their potential for sustainable agriculture and environmental management.

G-proteins↗
DOE OSTI2023

The Development of the Pooled Rideshare Acceptance Model (PRAM)

Due to the advancements in real-time information communication technologies and sharing economies, rideshare services have gained significant momentum by offering dynamic and/or on-demand services. Rideshare service companies evolved from personal rideshare, where riders traveled solo or with known individuals, into pooled rideshare (PR), where riders can travel with one to multiple unknown riders. Similar to other shared economy services, pooled rideshare is beneficial as it efficiently utilizes resources, resulting in reduced energy usage, as well as reduced costs for the riders. However, previous research has demonstrated that riders have concerns about using pooled rideshare, especially regarding personal safety. A U.S. national survey with 5385 participants was used to understand human factor-related barriers and user preferences to develop a novel Pooled Rideshare Acceptance Model (PRAM). This model used a covariance-based structural equation model (CB-SEM) to identify the relationships between willingness to consider PR factors (time/cost, privacy, safety, service experience, and traffic/environment) and optimizing one’s experience of PR factors (vehicle technology/accessibility, convenience, comfort/ease of use, and passenger safety), resulting in the higher-order factor trust service. We examined the factors’ relative contribution to one’s willingness/attitude towards PR and user acceptance of PR. Privacy, safety, trust service, and convenience were statistically significant factors in the model, as were the comfort/ease of use factor and the service experience, traffic/environment, and passenger safety factors. The only two non-significant factors in the model were time/cost and vehicle technology/accessibility; it is only when a rider feels safe that individuals then consider the additional non-significant variables of time, cost, technology, and accessibility. Privacy, safety, and service experience were factors that discouraged the use of PR, whereas the convenience factor greatly encouraged the acceptance of PR. Despite the time/cost factor’s lack of significance, individual items related to time and cost were crucial when viewed within the context of convenience. This highlights that while user perceptions of privacy and safety are paramount to their attitude towards PR, once safety concerns are addressed, and services are deemed convenient, time and cost elements significantly enhance their trust in pooled rideshare services. This study provides a comprehensive understanding of user acceptance of PR services and offers actionable insights for policymakers and rideshare companies to improve their services and increase user adoption.

dynamic rideshare system↗
DOE OSTI2017

Prospects for Measuring Abundances of >20 Elements with Low-resolution Stellar Spectra

Understanding the evolution of the Milky Way calls for the precise abundance determination of many elements in many stars. A common perception is that deriving more than a few elemental abundances ([Fe/H], [ α /Fe], perhaps [C/H], [N/H]) requires medium-to-high spectral resolution, R ≳ 10,000, mostly to overcome the effects of line blending. In a recent work, we presented an efficient and practical way to model the full stellar spectrum, even when fitting a large number of stellar labels simultaneously. In this paper, we quantify to what precision the abundances of many different elements can be recovered, as a function of spectroscopic resolution and wavelength range. In the limit of perfect spectral models and spectral normalization, we show that the precision of elemental abundances is nearly independent of resolution, for a fixed exposure time and number of detector pixels; low-resolution spectra simply afford much higher S/N per pixel and generally larger wavelength range in a single setting. We also show that estimates of most stellar labels are not strongly correlated with one another once R ≳ 1000. Modest errors in the line-spread function, as well as small radial velocity errors, do not affect these conclusions, and data-driven models indicate that spectral (continuum) normalization can be achieved well enough in practice. These results, to be confirmed with an analysis of observed low-resolution data, open up new possibilities for the design of large spectroscopic stellar surveys and for the reanalysis of archival low-resolution data sets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Wavelet-based Characterization of Small-scale Solar Emission Features at Low Radio Frequencies

Low radio frequency solar observations using the Murchison Widefield Array have recently revealed the presence of numerous weak short-lived narrowband emission features, even during moderately quiet solar conditions. These nonthermal features occur at rates of many thousands per hour in the 30.72 MHz observing bandwidth, and hence necessarily require an automated approach for their detection and characterization. Here, we employ continuous wavelet transform using a mother Ricker wavelet for feature detection from the dynamic spectrum. We establish the efficacy of this approach and present the first statistically robust characterization of the properties of these features. In particular, we examine distributions of their peak flux densities, spectral spans, temporal spans, and peak frequencies. We can reliably detect features weaker than 1 SFU, making them, to the best of our knowledge, the weakest bursts reported in literature. The distribution of their peak flux densities follows a power law with an index of −2.23 in the 12–155 SFU range, implying that they can provide an energetically significant contribution to coronal and chromospheric heating. These features typically last for 1–2 s and possess bandwidths of about 4–5 MHz. Their occurrence rate remains fairly flat in the 140–210 MHz frequency range. At the time resolution of the data, they appear as stationary bursts, exhibiting no perceptible frequency drift. These features also appear to ride on a broadband background continuum, hinting at the likelihood of them being weak type-I bursts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

ODIN: Characterizing the Three-dimensional Structure of Two Protocluster Complexes at z = 3.1

We present a detailed study of the 3D morphology of two extended associations of multiple protoclusters at z = 3.1. These protocluster "complexes," designated COSMOS-z3.1-A and COSMOS-z3.1-C, are the most prominent overdensities of z = 3.1 Lyα emitters (LAEs) identified in the COSMOS field by the One-hundred-deg$^{2}$ DECam Imaging in Narrowbands survey. These protocluster complexes have been followed up with extensive spectroscopy from Keck, Gemini, and DESI. Using a probabilistic method that combines photometrically selected and spectroscopically confirmed LAEs, we reconstruct the 3D structure of these complexes on scales of ≈50 cMpc. We validate our reconstruction method using the IllustrisTNG300-1 cosmological hydrodynamical simulation and show that it consistently outperforms approaches relying solely on spectroscopic data. The resulting 3D maps reveal that both complexes are irregular and elongated along a single axis, emphasizing the impact of sightline on our perception of structure morphology. The complexes consist of multiple density peaks, 10 in COSMOS-z3.1-A and 4 in COSMOS-z3.1-C. The former is confirmed to be a proto-supercluster, similar to Hyperion at z = 2.4 but observed at an even earlier epoch. Multiple "tails" connected to the cores of the density peaks are seen, likely representing cosmic filaments feeding into these extremely overdense regions. The 3D reconstructions further provide strong evidence that Lyα blobs preferentially reside in the outskirts of the highest density regions. Descendant mass estimates of the density peaks suggest that COSMOS-z3.1-A and COSMOS-z3.1-C will evolve to become ultramassive structures by z = 0, with total masses log ( M / M ,⊙ ,) ≳ 15.3 , exceeding that of Coma.

Ramakrishnan, Vandana [Purdue U., West Lafayette] ↗
DOE OSTI2023

Opinions from Users Across the Lifespan about Fully Autonomous and Rideshare Vehicles with Associated Features

Fully autonomous vehicles have the potential to fundamentally transform the future transportation system. While previous research has examined individuals’ perceptions towards fully autonomous vehicles, a complete understanding of attitudes and opinions across the lifespan is unknown. Therefore, individuals’ awareness, acceptance, and preferences towards autonomous vehicles were obtained from 75 participants through interviews with three diverse groups of participants: 20 automotive engineering graduate students who were building an autonomous concept vehicle, 21 non-technical adults, and 34 senior citizens. The results showed that regardless of age, an individual’s readiness to ride in a fully autonomous vehicle and the vehicle’s requirements were influenced by the users’ understanding of autonomous vehicles. All of the engineering students understand what a fully autonomous vehicle is and this group was the most willing to ride especially compared to the seniors, where only half of the seniors knew what a fully autonomous vehicle is and 58.8% were not at all ready to ride one. The desire to have a manual control option or the ability to override the vehicle was common (90% of the engineering students, 95.2% of the adults, and 82.4% of the seniors), especially for individuals who reported not being ready to ride in a fully autonomous vehicle. The majority of all three groups of participants (85% of the engineering students, 81% of the adults, and 52.9% of the seniors) considered it essential that the vehicle should convey information about the vehicle’s status and intended behavior. Diagnostic information about the vehicle was desired by the engineering students (71.4%), who had a technical understanding of autonomous vehicles and current automotive related technologies. When autonomous vehicles are available, most participants anticipate preferring to use them as a rideshare service model (75% of the engineering students, 38% of the adults, and 27% of the seniors) rather than owning (5% of the engineering students, 19% of the adults, and 21% of the seniors) the autonomous vehicle themselves. Regarding the topic of sharing rides with strangers, both the automotive engineering students (90%) and the adults (52.6%) were comfortable with the idea of pooled rideshare in comparison to the seniors (29.4%). In future efforts, it will be important to include potential autonomous vehicle users of a wide age range as well as physical, cognitive, and visual abilities.

Gangadharaiah, Rakesh↗
DOE OSTI2017

Fires Following Bark Beetles: Factors Controlling Severity and Disturbance Interactions in Ponderosa Pine

Previous studies have suggested that bark beetles and fires can be interacting disturbances, whereby bark beetle–caused tree mortality can alter the risk and severity of subsequent wildland fires. However, there remains considerable uncertainty around the type and magnitude of the interaction between fires following bark beetle attacks, especially in drier forest types such as those dominated by ponderosa pine (Pinus ponderosa Lawson & C. Lawson). We used a full factorial design across a range of factors thought to control bark beetle-fire interactions, including the temporal phase of the outbreak, level of mortality, and wind speed. We used a three-dimensional physics-based model, HIGRAD/FIRETEC, to simulate fire behavior in fuel beds representative of 60 field plots across five national forests in northern Arizona, USA. The plots were dominated by ponderosa pine, and encompassed a gradient of bark beetle–caused mortality due to a mixture of both Ips and Dendroctonus species. Non-host species included two sprouting species, Gambel oak (Quercus gambelii Nutt.) and alligator juniper (Juniperus deppeana Steud.), as well as other junipers and pinyon pine (Pinus edulis Engelm.). The simulations explicitly accounted for the modifications of fuel mass and moisture distribution caused by bark beetle–caused mortality. We first analyzed the influence of the outbreak phase, level of mortality, and wind speed on the severity of a subsequent fire, expressed as a function of live and dead canopy fuel consumption. We then computed a metric based on canopy fuel loss to characterize whether bark beetles and fire are linked disturbances and, if they are, if the linkage is antagonistic (net bark beetle and fire severity being less than if the two disturbances occurred independently) or synergistic (greater combined effects than independent disturbances). Both the severity of a subsequent fire and whether bark beetles and fire are linked disturbances depended on the outbreak phase of the bark beetle mortality and attack severity, as well as the fire weather (here, wind). Greater fire severity and synergistic interactions were generally associated with the “red phase” (when dead needles remain on trees). In contrast, during the “gray phase” (when dead needles had fallen to the ground), fire severity was either similar to, or less than, green-phase fires and interactions were generally antagonistic, but included both synergistic and neutral interactions. The simulations also revealed that the magnitude of the linkage between these two disturbances was smaller for fires occurring during high wind conditions, especially in the red phase. This complexity might be a reason for the contrasted or controversial perception of bark beetle-fire interactions reported in the literature, since both fire severity and the type and magnitude of the linkage can vary strongly among studies. These results suggest that, for fires burning in the gray phase following moderate levels of mortality, bark beetle–caused mortality may buffer rather than exacerbate fire severity. However, for fires burning under high wind speeds, regardless of the outbreak phase or level of mortality, the near complete loss of canopy fuels may push this ecosystem into an alternative state dominated by sprouting species.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Optimizing stadium evacuation by integrating geocomputation and affordance theory

Football is culturally and economically important in the United States, and football stadiums are part of the country's critical infrastructure, thus receiving government protection against hazard events. In this project, an agent-based evacuation model was implemented to optimize evacuation time from The University of Southern Mississippi's M.M. Roberts Stadium (football) by accounting for evacuees’ age, gender, physical fitness, alcohol consumption, and prior experience with hazard events. The findings revealed that (i) the age and gender of an individual impact his/her locomotion speed and (ii) evacuation route choice is influenced by evacuees’ perception of its safety and effectiveness. The estimated evacuation times for all evacuees to exit only the stadium and the stadium plus the surrounding campus were 20.82 and 165.01 minutes, respectively. Both of these times were shorter than the evacuation times determined by models employing location-unspecific locomotion speeds. One-way analysis of variance revealed that there were statistically significant differences between use of location-specific and location-unspecific within-stadium evacuation times (p ≤ 0.001 with α = 0.05). These results suggest that using local data is vital to accurately estimate evacuation time.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Induced seismicity in geologic carbon storage

Geologic carbon storage, as well as other geo-energy applications, such as geothermal energy, seasonal natural gas storage and subsurface energy storage imply fluid injection and/or extraction that causes changes in rock stress field and may induce (micro)seismicity. If felt, seismicity has a negative effect on public perception and may jeopardize wellbore stability and damage infrastructure. Thus, induced earthquakes should be minimized to successfully deploy geo-energies. However, numerous processes may trigger induced seismicity, which contribute to making it complex and translates into a limited forecast ability of current predictive models. We review the triggering mechanisms of induced seismicity. Specifically, we analyze (1) the impact of pore pressure evolution and the effect that properties of the injected fluid have on fracture and/or fault stability; (2) non-isothermal effects caused by the fact that the injected fluid usually reaches the injection formation at a lower temperature than that of the rock, inducing rock contraction, thermal stress reduction and stress redistribution around the cooled region; (3) local stress changes induced when low-permeability faults cross the injection formation, which may reduce their stability and eventually cause fault reactivation; (4) stress transfer caused by seismic or aseismic slip; and (5) geochemical effects, which may be especially relevant in carbonate-containing formations. We also review characterization techniques developed by the authors to reduce the uncertainty in rock properties and subsurface heterogeneity both for the screening of injection sites and for the operation of projects. Based on the review, we propose a methodology based on proper site characterization, monitoring and pressure management to minimize induced seismicity.

58 GEOSCIENCES↗
DOE OSTI2026

Data Driven Approach to Public Opinion Mining on Autonomous Vehicles: Sentiment Analysis of Social Media Comments Using Large Language Models

In the realm of online identity, social media has emerged as a rich and dynamic source of user-generated content, making it an invaluable resource for understanding public sentiment on a wide range of topics. Individuals often share their raw emotions and candid opinions on these platforms without fear of judgment or backlash. In this study, we conduct a sentiment analysis on user comments collected from various online platforms, with a specific focus on discussions surrounding autonomous vehicles. Leveraging the capabilities of large language models (LLMs), we classify each comment into one of five sentiment categories: Very Negative, Negative, Neutral, Positive, and Very Positive. Our approach demonstrates the effectiveness of LLMs in capturing nuanced contextual sentiment, offering a scalable and state-of-the-art alternative to traditional manual annotation methods. The results reveal key trends and insights into public perception, enabling a deeper understanding of how autonomous vehicle technologies are received by the online community. Our findings underscore the dynamic nature of public sentiment, which is shaped not only by advances in autonomous vehicle technology but also by contextual events such as regulatory developments, political adjustment and safety incidents.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Visualization for Insight and Data Analysis in Energy Research

This talk explores how advanced visualization technologies are transforming analytical reasoning and knowledge discovery in energy research, drawing on recent work at the National Laboratory of the Rockies' Computational Science Center. Through a series of scientific case studies, we demonstrate how immersive and high-resolution visualization environments enable scientists and engineers to identify previously unseen patterns and features - insights that often remain hidden in traditional desktop-based analysis. By embedding richer information into interactive analytics tools, these approaches support the exploration of complex, multivariate parameter spaces, where interaction itself catalyzes understanding. Beyond capability, we emphasize the critical role of visualization design grounded in perception and cognition, showing how visual encodings directly influence analytical outcomes. Spanning applications from materials science to integrated energy systems, these visualization approaches accelerate innovation and improve decision-making by enabling deeper, more reliable insight into increasingly complex energy data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

From molecular manipulation of domesticated Chlamydomonas reinhardtii to survival in nature

In the mid-20th century, the unicellular and genetically tractable green alga Chlamydomonas reinhardtii was first developed as a model organism to elucidate fundamental cellular processes such as photosynthesis, light perception and the structure, function and biogenesis of cilia. Various studies of C. reinhardtii have profoundly advanced plant and cell biology, and have also impacted algal biotechnology and our understanding of human disease. However, the 'real' life of C. reinhardtii in the natural environment has largely been neglected. To extend our understanding of the biology of C. reinhardtii, it will be rewarding to explore its behavior in its natural habitats, learning more about its abundance and life cycle, its genetic and physiological diversity, and its biotic and abiotic interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

A florigen paralog is required for short-day vernalization in a pooid grass

Perception of seasonal cues is critical for reproductive success in many plants. Exposure to winter cold is a cue that can confer competence to flower in the spring via a process known as vernalization. In certain grasses, exposure to short days is another winter cue that can lead to a vernalized state. In Brachypodium distachyon, we find that natural variation for the ability of short days to confer competence to flower is due to allelic variation of the FLOWERING LOCUS T (FT1) paralog FT-like9 (FTL9). An active FTL9 allele is required for the acquisition of floral competence, demonstrating a novel role for a member of the FT family of genes. Loss of the short-day vernalization response appears to have arisen once in B. distachyon and spread through diverse lineages indicating that this loss has adaptive value, perhaps by delaying spring flowering until the danger of cold damage to flowers has subsided.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Incorporating Human Readiness Levels at Sandia National Laboratories

Since 2010, the concept of human readiness levels has been under development as a possible supplement to the existing technology readiness level (TRL) scale. The intent is to provide a mechanism to address safety and performance risks associated with the human component in a system that parallels the TRL structure already familiar to the systems engineering community. Sandia National Laboratories in Albuquerque, New Mexico, initiated a study in 2015 to evaluate options to incorporate human readiness planning for Sandia processes and products. The study team has collected the majority of baseline assessment data and has conducted interviews to understand staff perceptions of four different options for human readiness planning. Preliminary results suggest that all four options may have a vital role, depending on the type of work performed and the phase of product development. Upon completion of data collection, the utility of identified solutions will be assessed in one or more test cases.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗