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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Detection of quasar feedback from the thermal Sunyaev–zel’dovich effect in Planck

Poorly understood feedback processes associated with highly luminous black hole accretion in quasars may dramatically affect the properties of their host galaxies. We search for the effect of quasar feedback on surrounding gas using Planck maps of the thermal Sunyaev–Zel’dovich effect (tSZ). By stacking tSZ Compton-y maps centered on the locations of 26,686 spectroscopic quasars from the Sloan Digital Sky Survey, we detect a strong but unresolved tSZ Compton-y signal at >5σ significance that likely originates from a combination of virialized halo atmosphere gas and quasar feedback effects. We show that the feedback contribution to our detected quasar tSZ signal is likely to dominate over virialized halo gas by isolating the feedback tSZ component for high- and low-redshift quasars. We find that this quasar tSZ signal also scales with black hole mass and bolometric luminosity, all consistent with general expectations of quasar feedback. We estimate the mean angularly integrated Compton-y of quasars at z ≃ 1.5 to be 3.5 × 10{sup −6} Mpc{sup 2}, corresponding to mean total thermal energies in feedback and virialized halo gas of 1.1(±0.2)×10{sup 62} erg, and discuss the implications for quasar feedback. If confirmed, the large total thermal feedback energetics we estimate to be 5% (±1% statistical uncertainty) of the black hole mass will have important implications for the effects of quasar feedback on the host galaxy, as well as the surrounding intergalactic medium.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2023

ENSO Disrupts Boreal Winter CRE Feedback

Twenty years of satellite-based cloud and radiation observations allow us to examine the observed cloud radiative effect (CRE) feedback (i.e., CRE change per unit change in global mean surface temperature). By employing a decomposition method to separate the contribution of “internal changes” and “relative-frequency-of-occurrence (RFO) changes” of distinct cloud regime (CR) groups, notable seasonal contrasts of CRE feedback characteristics emerge. Boreal winter CRE feedback is dominated by the positive shortwave CRE (SWCRE) feedback of oceanic low-thick clouds, due to their decreasing RFO as temperature rises. This signal is most likely due to El Niño-Southern Oscillation (ENSO) activity. When ENSO signals are excluded, boreal winter CRE feedback becomes qualitatively similar to the boreal summer feedback, where several CR groups contribute to the total CRE feedback more evenly. Most CR groups’ CRE feedbacks largely come from changing RFO: e.g., the predominant transition from oceanic cumulus to broken clouds and more occurrences of higher convective clouds with warming temperature. At the same time, low-thick and broken clouds experience optical thinning and decreasing cloud fraction, and these features are more prominent in boreal summer than winter. Overall, the seasonally asymmetric patterns of CRE feedback, primarily due to ENSO, introduce complexity in assessments of CRE feedback.

ENSO↗
DOE OSTI2023

Mesoscale system feedback-induced dissipation and noise suppression

A high-gain and low-noise negative feedback control (“feedback control”) system can detect charge transfer in quantum systems at room temperatures. The feedback control system can attenuate dissipative coupling between a quantum system and its thermodynamic environment. The feedback control system can be integrated with standard commercial voltage-impedance measurement system, for example, a potentiostat. In one aspect, the feedback control system includes a plurality of electrodes that are configured to electrically couple to a sample, and a feedback mechanism coupled to a first electrode of the plurality of electrodes. The feedback mechanism is configured to detect a potential associated with the sample via the first electrode. The feedback mechanism provides a feedback signal to the sample via a second electrode of the plurality of electrodes, the feedback signal is configured to provide excitation control of the sample at a third electrode of the plurality of electrode.

Gupta, Chaitanya↗
DOE OSTI2025

Decomposing Cloud Radiative Feedbacks by Cloud-Top Phase

Changes in cloud scattering properties and emissivity that arise from atmospheric warming cause substantial radiative feedbacks in model projections of anthropogenic climate change, and the relative importance of the underlying mechanisms is poorly understood. One leading hypothesis is that ice-to-liquid conversions cause clouds to optically thicken, producing a major negative feedback. We test this hypothesis by developing a method to decompose cloud radiative feedbacks by cloud-top phase. The method is applied to an ensemble of six state-of-the-art global climate models run with prescribed sea surface temperature. In these simulations, the global mean of the net cloud scattering and emissivity feedback from cloud-phase conversions ranges from −0.17 to −0.01 W m −2 K −1 , while the overall net cloud feedback ranges from 0.02 to 0.91 W m −2 K −1 . The multimodel mean of the cloud scattering and emissivity feedback from cloud-phase conversions is approximately 19% of the magnitude of the multimodel mean of the overall cloud feedback (−0.10 vs 0.52 W m −2 K −1 ). These results indicate that cloud-phase conversions cause a robust negative feedback by changing cloud scattering and emissivity, but this mechanism makes a modest contribution to the overall cloud feedback at the global scale.

Climate change↗
DOE OSTI2022

Evaluating Climate Models’ Cloud Feedbacks Against Expert Judgment

Abstract The persistent and growing spread in effective climate sensitivity (ECS) across global climate models necessitates rigorous evaluation of their cloud feedbacks. Here we evaluate several cloud feedback components simulated in 19 climate models against benchmark values determined via an expert synthesis of observational, theoretical, and high‐resolution modeling studies. We find that models with smallest feedback errors relative to these benchmark values generally have moderate total cloud feedbacks (0.4–0.6 W m −2 K −1 ) and ECS (3–4 K). Those with largest errors generally have total cloud feedback and ECS values that are too large or too small. Models tend to achieve large positive total cloud feedbacks by having several cloud feedback components that are systematically biased high rather than by having a single anomalously large component, and vice versa. In general, better simulation of mean‐state cloud properties leads to stronger but not necessarily better cloud feedbacks. The Python code base provided herein could be applied to developmental versions of models to assess cloud feedbacks and cloud errors and place them in the context of other models and of expert judgment in real‐time during model development.

58 GEOSCIENCES↗
DOE OSTI2015

On the interplay between star formation and feedback in galaxy formation simulations

We investigate the star formation–feedback cycle in cosmological galaxy formation simulations, focusing on the progenitors of Milky Way (MW)-sized galaxies. We find that in order to reproduce key properties of the MW progenitors, such as semi-empirically derived star formation histories (SFHs) and the shape of rotation curves, our implementation of star formation and stellar feedback requires (1) a combination of local early momentum feedback via radiation pressure and stellar winds, and subsequent efficient supernovae feedback, and (2) an efficacy of feedback that results in the self-regulation of the global star formation rate on kiloparsec scales. We show that such feedback-driven self-regulation is achieved globally for a local star formation efficiency per free fall time of ϵ{sub ff}≈10%. Although this value is larger that the ϵ{sub ff}∼1% value usually inferred from the Kennicutt–Schmidt (KS) relation, we show that it is consistent with direct observational estimates of ϵ{sub ff} in molecular clouds. Moreover, we show that simulations with local efficiency of ϵ{sub ff}≈10% reproduce the global observed KS relation. Such simulations also reproduce the cosmic SFH of the MW-sized galaxies and satisfy a number of other observational constraints. Conversely, we find that simulations that a priori assume an inefficient mode of star formation, instead of achieving it via stellar feedback regulation, fail to produce sufficiently vigorous outflows and do not reproduce observations. This illustrates the importance of understanding the complex interplay between star formation and feedback, and the detailed processes that contribute to the feedback-regulated formation of galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Deterministic generation of remote entanglement with active quantum feedback

We develop and study protocols for deterministic remote entanglement generation using quantum feedback, without relying on an entangling Hamiltonian. In order to formulate the most effective experimentally feasible protocol, we introduce the notion of average-sense locally optimal feedback protocols, which do not require real-time quantum state estimation, a difficult component of real-time quantum feedback control. We use this notion of optimality to construct two protocols that can deterministically create maximal entanglement: a semiclassical feedback protocol for low-efficiency measurements and a quantum feedback protocol for high-efficiency measurements. The latter reduces to direct feedback in the continuous-time limit, whose dynamics can be modeled by a Wiseman-Milburn feedback master equation, which yields an analytic solution in the limit of unit measurement efficiency. Our formalism can smoothly interpolate between continuous-time and discrete-time descriptions of feedback dynamics and we exploit this feature to derive a superior hybrid protocol for arbitrary nonunit measurement efficiency that switches between quantum and semiclassical protocols. Lastly, we show using simulations incorporating experimental imperfections that deterministic entanglement of remote superconducting qubits may be achieved with current technology using the continuous-time feedback protocol alone.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Spectral Signatures of Moisture–Convection Feedbacks over the Indian Ocean

Abstract Positive feedbacks between the cloud population and the environmental moisture field are central to theoretical expositions on the Madden–Julian oscillation (MJO). This study investigates the statistical incidence of positive moisture–convection feedbacks across multiple space and time scales over the tropical Indian Ocean. This work uses vertically integrated moisture budget terms from the ECMWF interim reanalysis [ERA-Interim (ERA-I)] in a framework proposed by Hannah et al. Positive moisture–convection feedbacks are primarily a low-frequency, low-wavenumber phenomenon with significant spectral signatures in the 32–48-day time scale. The efficacy of these feedbacks, however, is subject to horizontal moisture advection variations, whose relative importance varies with scale. Wave-filtered Tropical Rainfall Measuring Mission (TRMM) satellite precipitation is used to show that these moisture–convection feedbacks contribute more to moisture increases in the MJO than in other equatorial waves. A moving-window correlation analysis suggests that instances of moisture–convection feedbacks are more frequent in drier conditions, when column water vapor (CWV) is below its climatological mean value, with the implication that positive moisture–convection feedbacks shape the mean CWV field by moistening drier air columns, but that they are less effective in moistening already moist environments. Ground radar observations show that stratiform rain damps local CWV increases on short time scales (<2 days) and therefore precludes positive moisture–convection feedbacks in high-CWV environments. Vertical coherence structures from ERA-I confirm that relatively bottom-heavy cloud ensembles (i.e., peaks between 700 and 850 hPa) are more effective in inducing low-frequency positive moisture–convection feedbacks than ensembles with other vertical structures. Low-frequency horizontal advective drying damps moisture increases and is strongly coherent with upper-level rising motion.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Shortwave feedbacks and El Nino-Southern Oscillation: Forced ocean coupled ocean-atmosphere experiments

Changes in tropical sea surface temperature (SST) can produce changes in cloudiness that modify incoming solar shortwave (SW) radiation, which in turn affects SST. The effects of this negative feedback on Pacific interannual variability are examined in forced ocean model and hybrid coupled ocean-atmosphere model simulations. Two empirical schemes are used to model the large-scale, low-frequency response of surface SW to SST anomalies. The first scheme attempts to account for the nonlocal nature of the atmospheric response to SST based patterns of covariability analyzed through singular value decomposition. In the observations the primary coupled mode of variability is composed of a SW anomaly in the central Pacific that covaries with anomalous SST in the eastern Pacific. This is applied in the model as a nonlocal feedback. The second scheme examines the effects of a purely local feedback with a spatially varying coefficient of magnitude chosen similar to the first scheme. In almost all cases the second scheme behaved similarly to the first, presumably because the correlation scale of SST is large enough for El Nino-Southern Oscillation (ENSO) dynamics that there is little sensitivity to the local approximation in the SW feedback. In simulations forced by time series of observed wind stress the SW feedback induced very minor SST damping. Results for a simpified heat budget analysis showed that while the SW feedback increased the local heat flux damping on SST, it also induced a mean shallowing of the mixed layer. The resulting changes in both the local mean vertical temperature gradient and the zonal velocity response to the wind stress acted to oppose the local heat flux damping effects. When the observed SW anomalies were applied to forced simulations, the simulated SST anomalies were modified as expected, and agreement with observed SST improved. In coupled simulations the SW feedbacks had greater impact than in the case of specified stress. The main effects were to decrease the magnitude of the warm and cold SST anomalies in the central Pacific, while leaving the pattern and evolution of ENSO anomalies essentially unchanged elsewhere. The SW feedbacks thus produce a modest improvement of the model ENSO SST pattern compared with observations, although they tended to shorten the period of the model ENSO cycle. Overall the results suggest that large-scale SW feedbacks are of quantitative importance to simulating some aspects of the ENSO cycle but are not critical to the overall occurrence of the phenomenon.

Waliser, Duane E.↗
NASA NTRSDate not supplied

On the Nature of the Arctic’s Positive Lapse-rate Feedback: Cause or Symptom of Arctic Amplification

Radiative energy fluxes exiting the atmosphere towards the surface and to space are sensitive to the vertical structure of temperature. Under anthropogenic forcing, this sensitivity gives rise to the lapse-rate feedback. Shown to be negative in the tropics and positive in the Arctic, studies argue that the lapse-rate feedback is the primary cause of Arctic Amplification. While mechanistically the negative tropical lapse-rate feedback is understood, the mechanics of the positive Arctic lapse-rate feedback are less clear. Previous arguments state that the Arctic’s stable stratification is the origin of its positive lapse-rate feedback. We present results using CMIP5 and CMIP6 model output that arguing that the magnitude, spatial variability, seasonality, and inter-model spread in the Arctic lapse-rate feedback is controlled by surface properties and atmosphere-ocean-sea ice energy exchanges, not the degree of stable stratification. We argue that the Arctic’s positive lapse-rate feedback is a seasonal and regional phenomenon that manifests from local surface characteristics and surface albedo, ice insulation, and thermal inertia feedbacks that cause surface warming to outpace atmospheric warming in sea ice-retreat regions. We view the Arctic’s positive lapse-rate feedback as a symptom rather than the primary cause of Arctic Amplification.

Patrick Charles Taylor↗
NASA NTRSDate not supplied

On the Nature of the Arctic’s Positive Lapse Rate Feedback Cause or Symptom of Arctic Amplification

Radiative energy fluxes exiting the atmosphere towards the surface and to space are sensitive to the vertical structure of temperature. Under anthropogenic forcing, this sensitivity gives rise to the lapse-rate feedback. Shown to be negative in the tropics and positive in the Arctic, studies argue that the lapse-rate feedback is the primary cause of Arctic Amplification. While mechanistically the negative tropical lapse-rate feedback is understood, the mechanics of the positive Arctic lapse-rate feedback are less clear. Previous arguments state that the Arctic’s stable stratification is the origin of its positive lapse-rate feedback. We present results using CMIP5 and CMIP6 model output that arguing that the magnitude, spatial variability, seasonality, and inter-model spread in the Arctic lapse-rate feedback is controlled by surface properties and atmosphere-ocean-sea ice energy exchanges, not the degree of stable stratification. We argue that the Arctic’s positive lapse-rate feedback is a seasonal and regional phenomenon that manifests from local surface characteristics and surface albedo, ice insulation, and thermal inertia feedbacks that cause surface warming to outpace atmospheric warming in sea ice-retreat regions. We view the Arctic’s positive lapse-rate feedback as a symptom rather than the primary cause of Arctic Amplification.

Patrick C Taylor↗
DOE OSTI2024

The Interaction Between Climate Forcing and Feedbacks

A Perturbed Parameter Ensemble (PPE) with the Community Atmosphere Model version 6 (CAM6) is used to better understand the sensitivity of aerosol forcing and cloud feedbacks to changes in model processes. Aerosol forcing through aerosol-cloud interactions is mostly negative (a cooling) due to shortwave radiation, while feedbacks are positive or negative in different regions due to contrasting longwave and shortwave effects. Both forcing and feedbacks are related to the mean climate state. Higher magnitude cloud radiative effects generally mean larger magnitude net negative forcing and larger magnitude net positive feedback. Aerosol forcing is broadly related to the susceptibility of clouds to drop number. Feedbacks also related to susceptibility, but to a lesser extent and in different regions to aerosol forcing. Aerosol forcing and cloud feedbacks are anti-correlated in the CAM6 PPE such that stronger negative forcing is associated with stronger positive feedbacks. Even the processes governing forcing and feedback sensitivity in the PPE are similar. These include the warm rain formation process, ice loss processes and deep convective intensity.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

The effects of feedback lighting on the circadian drinking rhythm in the diurnal new world primate Saimiri sciureus

Feedback lighting provides illumination primarily during the subjective night (i.e., the photosensitive portion of the circadian cycle) in response to a given behavior. This technique has previously been used to test the nonparametric model of entrainment in nocturnal rodents. In three species (Rattus norvegicus, Mesocricetus auratus, and Mus musculus), the free-running period of the locomotor activity rhythm was similar whether the animals were exposed to continuous light or discrete light pulses occurring essentially only during the subjective night (i.e., feedback lighting). In the current experiments, feedback lighting was presented to squirrel monkeys so that light fell predominantly during the subjective night. Feedback lighting was linked to the drinking behavior in this diurnal primate so that when the animal drank, the lights went out. Despite the seemingly adverse predicament, the monkeys maintained regular circadian drinking rhythms. Furthermore, just as the period of the free-running activity rhythms of nocturnal rodents exposed to continuous light or feedback lighting were similar, the period of the drinking rhythms of the squirrel monkeys in continuous light and feedback lighting were comparable (25.6 +/- 0.1 and 25.9 +/- 0.1 hours, respectively), despite a substantial decrease in the total amount of light exposure associated with feedback lighting. The free-running period of monkeys exposed to continuous dark (24.5 +/- 0.1 hours) was significantly shorter than either of the two lighting conditions (P < 0.001). The results presented for the drinking rhythm were confirmed by examination of the temperature and activity rhythms. Therefore, discrete light pulses given predominately during the subjective night are capable of simulating the effects of continuous light on the free-running period of the circadian rhythms of a diurnal primate. The response of squirrel monkeys to feedback lighting thus lends further support for the model and suggests that the major entrainment mechanisms are similar in nocturnal rodents and diurnal primates.

NASA Discipline Number 40-30↗
NASA NTRS2017

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6.

The primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud-climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. However, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions 'How does the Earth system respond to forcing?' and 'What are the origins and consequences of systematic model biases?' and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity. A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO2 forcing and sea surface warming? CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. 1. How well do clouds and other relevant variables simulated by models agree with observations? 2. What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models? 3. Which models have the most credible representations of processes relevant to the simulation of clouds? 4. How do clouds and their changes interact with other elements of the climate system?

carbon dioxide↗
NASA NTRS2023

Comparison of Clouds and Cloud Feedback between AMIP5 and AMIP6

We examine the changes in clouds and cloud feedback between Phase 5 (AMIP5) and Phase 6 (AMIP6) of the Atmospheric Model Intercomparison Project. Each model is perturbed by uniformly increasing the sea surface temperature by 4 K. The simulated cloud fraction, the perturbed states and cloud radiative kernels are used to derive cloud feedback in the shortwave (SW), longwave (LW) and their sum (Net). Compared to AMIP5, the cloud fraction in AMIP6 increases by 9.1%, while the perturbation leads to a 0.25% decrease. The Net cloud feedback at the top of the atmosphere (TOA) is almost double (174%). Statistical tests support that this change is mainly due to an increase in the surface SW cloud feedback caused by optically thick, middle and low clouds. The contribution of the atmospheric Net component (12%) stems from the increase in the atmospheric LW cloud feedback, likely to play a role in weakening (strengthening) the northward (southward) meridional atmospheric energy transport, while the opposite is true for the surface LW and Net cloud feedback in the meridional oceanic energy transport. The substantial increase in cloud feedback at the TOA primarily contributes to the higher climate sensitivity. The cloud feedback spread in AMIP6 is comparable to that in AMIP5.

Clouds↗
DOE OSTI2026

Noise-canceling quantum feedback: Non-Hermitian dynamics with applications to state preparation and magic state distillation

Time-continuous quantum measurement allows for the tracking of a quantum system in real time via sequences of short, and individually weak, measurement intervals. Such measurements are necessarily invasive, imparting backaction to the system, and allowing the observer to update their state estimate based on stochastic measurement outcomes. Feedback control then involves real-time interventions by an observer, conditioned on the time-continuous measurement signal that they receive. Here, we consider here diffusive quantum trajectories and focus on the “noise-canceling” subset of feedback protocols that aim to minimize the degree of stochasticity in the dynamics. We derive such a class of feedback operations, showing that under the idealized assumptions of pure states, unit measurement efficiency, and zero time delay in implementing feedback operations, perfectly noise-canceling feedback always exists. We consider the resulting noise-canceled dynamics generated by an effective non-Hermitian Hamiltonian; while non-Hermitian Hamiltonians from continuous monitoring generally describe rare dynamics (accessible by costly postselection), the use of noise-canceling feedback here leads to non-Hermitian dynamics that occur deterministically. We demonstrate this via examples of entangled state preparation and stabilization. We then illustrate the potential for the application of noise cancellation to boost success rates in magic state distillation protocols. We show that adding feedback based on noise cancellation into a time-continuous five-to-one distillation protocol leads to higher probabilities of successful distillation across a range of input errors and increases the threshold on input errors for which the protocol is effective. Our results highlight the efficacy of noise-canceling feedback-aided protocols for quantum state preparation and stabilization tasks.

Karmakar, Tathagata [University of California, Ber↗
DOE OSTI2019

Cloud Radiative Feedbacks and El Niño–Southern Oscillation

Cloud radiative feedbacks are disabled via “cloud-locking” in the Community Earth System Model, version 1.2 (CESM1.2), to result in a shift in El Niño–Southern Oscillation (ENSO) periodicity from 2–7 years to decadal time scales. We hypothesize that cloud radiative feedbacks may impact the periodicity in three ways: by 1) modulating heat flux locally into the equatorial Pacific subsurface through negative shortwave cloud feedback on sea surface temperature anomalies (SSTA), 2) damping the persistence of subtropical southeast Pacific SSTA such that the South Pacific meridional mode impacts the duration of ENSO events, or 3) controlling the meridional width of off-equatorial westerly winds, which impacts the periodicity of ENSO by initiating longer Rossby waves. The result of cloud-locking in CESM1.2 contrasts that of another study, which found that cloud-locking in a different global climate model led to decreased ENSO magnitude across all time scales due to a lack of positive longwave feedback on the anomalous Walker circulation. CESM1.2 contains this positive longwave feedback on the anomalous Walker circulation, but either its influence on the surface is decoupled from ocean dynamics or the feedback is only active on interannual time scales. The roles of cloud radiative feedbacks in ENSO in other global climate models are additionally considered. In particular, it is shown that one cannot predict the role of cloud radiative feedbacks in ENSO through a multimodel diagnostic analysis. Instead, they must be directly altered.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Next Generation Environmentally-Friendly Driving Feedback Systems Research and Development

The objective of this project is to design, develop, and demonstrate a next-generation, federal safety- and emission-complaint driving feedback system that can be deployed across the existing vehicle fleet and improve fleet average fuel efficiency by at least 2%. The project objective was achieved with the driving feedback system that encourages fuel-efficient vehicle travel and operation through: 1) Eco-Routing Navigation module that suggests the most fuel-efficient route from one stop to the next, 2) Eco-Driving Feedback module that provides sensible information, recommendation, and warning regarding fuel-efficient vehicle operation, and 3) Eco-Score and Eco-Rank module that provides a means for driving performance tracking, self-evaluation, and peer comparison. The system also collects and stores vehicle travel and operation data, which are used by Algorithm Updating module to customize the other modules for specific vehicles and adapts them to specific drivers over time. The driving feedback system was designed and developed as an aftermarket technology that can be retrofitted to vehicles in the existing fleet. It consists of a mobile application for smart devices running Android operating system, a vehicle on-board diagnostics connector, and a data server. While the system receives and utilizes real-time vehicle and engine data from the vehicle’s controller area network bus through the vehicle’s on-board diagnostic connector, it does not modify or interfere with the vehicle’s controller area network bus, and thus, is in compliance with federal safety and emission regulations. The driving feedback system was demonstrated and then installed on 45 vehicles from three different fleets for field operational test. These include 15 private vehicles of the general public, 15 pickup trucks of the California Department of Transportation that are assigned to individual employees for business use, and 15 shuttle buses of the Riverside Transit Agency that are used for paratransit service. Detailed vehicle travel and operation data including route taken, driving speed, acceleration, braking, and the corresponding fuel consumption, were collected both before and during the test period. The data analysis results show that the fleet average fuel efficiency improvements for the three fleets with the use of the driving feedback system are in the range of 2% to 9%. The economic viability of the driving feedback system is high. A fully deployed system would require capital investment in smart device ($150-$350) and on-board diagnostics connector ($50-$100) as well as paying operating costs for wireless data plan and subscription fees ($20-$30 per month) for connecting to the data server and receiving various system services. For individual consumers who already own a smart device (such as smartphone) and commercial fleets that already use some kind of telematics services, the costs for deploying this driving feedback system would be much lower.

33 ADVANCED PROPULSION SYSTEMS↗