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The purpose of this testing was to characterize the pulsed-laser-induced single event effect (SEE) susceptibility of the Texas Instruments LM7171 voltage feedback amplifier. The test was conducted at the Naval Research Laboratory using their two-photon absorption (TPA) laser.
Effective climate sensitivity (EffCS), commonly estimated from model simulations with abrupt 4×CO 2 for 150 years, has been shown to depend on the CO 2 forcing level. To understand this dependency systematically, we performed a series of simulations with a range of abrupt CO 2 forcing in two climate models. Our results indicate that normalized EffCS values in these simulations are a non-monotonic function of the CO 2 forcing, decreasing between 3× and 4×CO 2 in CESM1-LE (2× and 3×CO 2 in GISS-E2.1-G) and increasing at higher CO 2 levels. The minimum EffCS value, caused by anomalously negative radiative feedbacks, arises mainly from sea-surface temperature (SST) relative cooling in the tropical and subtropical North Atlantic. This cooling is associated with the formation of the North Atlantic Warming Hole and Atlantic Meridional Overturning Circulation collapse under CO 2 forcing. Our findings imply that understanding changes in North Atlantic SST patterns is important for constraining near-future and equilibrium global warming.
Motion sickness is a common physiological reaction to provocative motion and is characterized by a constellation of symptoms, including stomach awareness, nausea, emesis, pallor, sweating, hypersalivation, and fatigue. The emergence of these symptoms can pose a significant threat to safety, particularly in the context of aviation. Given its prevalence among aviators and its detrimental impact on performance, researchers have endeavored to identify effective countermeasures for motion sickness. Currently, many of the existing interventions are pharmacological in nature and while effective, they present a problem due to their associated adverse side effects. A modified two-hour version of Autogenic Feedback Training Exercise (AFTE) could be an effective countermeasure to motion sickness without adverse side effects. AFTE combines principles of autogenic therapy, biofeedback, and learning to teach individuals to control their own internal physiological reactions through a series of relaxation and arousal exercises. AFTE was administered over six days. On the first day, participants were exposed to provocative motion via a rotating chair test to collect baseline physiological data. AFTE sessions were conducted on four consecutive days and lasted approximately 30 minutes each session. Participants were exposed to the rotating chair again on the 6th day. Results: Participants (n = 16) were evaluated on the number of rotations experienced and cumulative minutes spun in the chair. Participants tended to ride longer (M = 21.0 min, SD = 16.56) and tolerated more rotations (M = 244.8 rotations, SD = 310.62) on their second rotating chair test compared to baseline (M = 14.0 min, SD = 9.35; M = 125.8 rotations, SD = 124.08; t(15) = 2.21, p = .02). A moderate effect size was recorded (Hedges’s g = 0.44). A modified two-hour version of the AFTE is effective at increasing tolerance of symptoms associated with motion sickness.
INTRODUCTION: The development of Motion Sickness (MS) symptoms is correlated with increased sympathetic influence and irregular patterns of vagal activity. Such autonomic actions can be characterized by indices of heart rate variability (HRV), which reflect autonomic balance through neurocardiac function. Nonpharmacological interventions aimed at attenuating MS symptoms may therefore produce an effect on HRV. One such intervention that has been shown to mitigate MS symptoms is Autogenic Feedback Training Exercise (AFTE), which combines principles of autogenic therapy and biofeedback. AFTE teaches individuals to manipulate various physiological parameters in provocative environments and shows promise as a potential MS intervention in military aviators. The effects of AFTE on HRV have not previously been examined. Understanding HRV changes following AFTE may help to elucidate its indirect effects and inform its implementation for MS mitigation. METHODS: Twenty-four subjects received 2 hours of AFTE over 4 days. Pre- and post-AFTE rotating chair tests, which included stationary periods of baseline data, were conducted to evaluate the effects of AFTE. HRV data were recorded by SOMNOtouch™ NIBP. Post hoc analysis of pre- and post-AFTE short-term HRV (RMSSD, LF, HF, LF/HF) was performed. RESULTS: RMSSD, HF, and LF/HF were not significantly changed following AFTE. However, LF showed a statistically significant (p=0.015) decrease following AFTE. DISCUSSION: AFTE prescribes a respiratory rate of 15 breaths per minute (BPM), which is typically faster than participants’ pre-AFTE BPM (M=12.65). Healthy individuals can increase respiratory sinus arrhythmia (RSA) by slow, deep breathing. However, increasing the respiratory rate to 15 BPM may decrease RSA and subsequently HF. Increasing RSA potentially negates any influence of AFTE on HF, resulting in no significant change. RMSSD is correlated with HF power and was likewise not affected by AFTE. LF power, however, decreased significantly following AFTE, potentially indicating a lower sympathetic response in the post-AFTE measurement.
The recently completed RHIC fast global orbit feedback system uses 24 small 'window-frame' horizontal dipole correctors. Space limitations dictated a very compact design. The magnetic design and modelling of these laminated yoke magnets is described as well as the mechanical implementation, coil winding, vacuum impregnation, etc. Test procedures to determine the field quality and frequency response are described. The results of these measurements are presented and discussed. A small fringe field from each magnet, overlapping the opposite RHIC ring, is compensated by a correction winding placed on the opposite ring's magnet and connected in series with the main winding of the first one. Results from measurements of this compensation scheme are shown and discussed.
In order to correct beam perturbations in RHIC around 10Hz, a new fast data distribution network was required to deliver BPM position data at rates several orders of magnitude above the capability of the existing system. The urgency of the project limited the amount of custom hardware that could be developed, which dictated the use of as much commercially available equipment as possible. The selected architecture uses a custom hardware interface to the existing RHIC BPM electronics together with commercially available Gigabit Ethernet switches to distribute position data to devices located around the collider ring. Using the minimum Ethernet packet size and a field programmable gate array (FPGA) based state machine logic instead of a software based driver, real-time and deterministic data delivery is possible using Ethernet. The method of adapting this protocol for low latency data delivery, bench testing of Ethernet hardware, and the logic to construct Ethernet packets using FPGA hardware will be discussed. A robust communications system using almost all commercial off-the-shelf equipment was developed in under a year which enabled retrofitting of the existing RHIC BPM system to provide 10 KHz data delivery for a global orbit feedback scheme using 72 BPMs. Total latencies from data acquisition at the BPMs to delivery at the controller modules, including very long transmission distances, were kept under 100 {micro}s, which provide very little phase error in correcting the 10 Hz oscillations. Leveraging off of the speed of Gigabit Ethernet and wide availability of Ethernet products enabled this solution to be fully implemented in a much shorter time and at lower cost than if a similar network was developed using a proprietary method.
Electron cloud (ecloud) and transverse mode coupled-bunch instabilities (TMCI) limit the bunch intensity in the CERN SPS. This paper presents experimental measurements in the SPS of single-bunch motion driven by a GHz bandwidth vertical excitation system. The final goal is to quantify the change in internal bunch dynamics as instability thresholds are approached, and quantify the frequencies of internal modes as ecloud effects become significant. Initially, we have been able to drive the beam and view its motion. We show the excitation of barycentric, head-tail and higher vertical modes at different bunch intensities. The beam motion is analyzed in the time domain, via animated presentations of the sampled vertical signals, and in the frequency domain, via spectrograms showing the modal frequencies vs. time. The demonstration of the excitation of selected internal modes is a significant step in the development of the feedback control techniques.
A 4.2 GS/sec. beam excitation system with accelerator synchronization and power stages is described. The system is capable of playing unique samples (32 samples/bunch) for 15,000 turns on selected bunch(es) in the SPS in syn- chronism with the injection and acceleration cycle. The purpose of the system is to excite internal modes of single-bunch vertical motion, and study the bunch dynamics in the presence of developing Electron cloud or TMCI effects. The system includes a synchronized master oscillator, SPS timing functions, an FPGA based arbitrary waveform generator, 4.2 GS/sec. D/A system and four 80W 20-1000 MHz amplifiers driving a tapered stripline pickup/kicker. A software GUI allows specification of various modulation signals, selection of bunches and turns to excite, while a remote control interface allows simple control/monitoring of the RF power stages located in the tunnel. The successful use of this system for SPS MD measurements in 2011 is a vital proof-of-principle for wideband feedback using similar functions to correct the beam motion.
The SPS at high intensities exhibits transverse single bunch instabilities with signatures consistent with an Ecloud driven instability. We present recent MD data from the SPS, details of the instrument technique and spectral analysis methods which help reveal complex vertical motion that develops within a subset of the injected bunch trains. The beam motion is detected via wideband exponential taper striplines and delta-sigma hybrids. The raw sum and difference data is sampled at 50 GHz with 1.8 GHz bandwidth. Sliding window FFT techniques and RMS motion techniques show the development of large vertical tune shifts on portions of the bunch of nearly 0.025 from the base tune of 0.185. Results are presented via spectrograms and bunch slice trajectories to illustrate development of the unstable beam and time scale of development along the injected bunch train. The study shows that the growing unstable motion occupies a very broad frequency band of 1.2 GHz. These measurements are compared to numerical simulation results, and the system parameter implications for an Ecloud feedback system are outlined.
Measurements of the beam position along an accelerator are typically treated equally using standard SVD-based orbit correction algorithms so distributing the residual errors, modulo the local beta function, equally at the measurement locations. However, sometimes a more stable orbit at select locations is desirable. In this paper, we introduce an algorithm for weighting the beam position measurements to achieve a more stable local orbit. The results of its application to close-orbit correction and 10 Hz orbit feedback are presented.
This report briefly reviews past research and describes a two year pilot evaluation of a low cost residential energy feedback system installed in twenty case study homes in Florida.
Dependency of the transport sector on fossil fuels is encouraging a significant amount of research in to improving fuel efficiency in vehicles. Three primary techniques are identified for vehicle fuel efficiency improvement: 1) vehicle technology improvements such as drivetrain improvements, 2) traffic infrastructure improvements such as traffic flow management and route selection, and 3) driver behavior changes such as acceleration and deceleration profiles. Out of the 3 techniques, driver behavior changing has the least implementation cost and is able to provide immediate results. Thus, this paper presents a fuel efficient driving behavior identification and feedback architecture that is specific to fleet vehicles. The presented method utilizes historical data from fleet drivers on specific routes and generates fuel optimal velocity profiles that do not affect travel time. The identified velocity profile is the prompted to the driver via a low-cost plug-and-play style un-obstructive display. The display uses an intuitive and easily understandable visualization to prompt drivers on fuel efficient velocity. The presented architecture was tested on the Idaho National Laboratory (INL) bus fleet in real-world driving conditions and was shown to be able to increase the fuel economy by 9% and 20% in two different driving scenarios.
The critical diffusion equation with feedback is investigated within the context of steady-state multiphysics. It is proposed that for critical configurations there is no need to include the multiplication factor k in the formulation of the diffusion equation. This is notable because exclusion of k from the coupled system of equations precludes the mathematically tenuous notion of a nonlinear eigenvalue problem. On the other hand, it is shown that if the factor k is retained in the diffusion equation, as is currently common practice, then the resulting problem is equivalent to the constrained minimization of a functional representing the critical equilibrium of neutron and temperature distributions. The unconstrained solution corresponding to k = 1 represents the natural equilibrium of a critical system at steady-state. Computational methods for solving the constrained problem (with k) are briefly reviewed from the literature and a method for the unconstrained problem (without k) is outlined. A numerical example is studied to examine the effects of the constraint in the nonlinear system. (authors)
Conduits are ubiquitous and critical pathways for many fluids relevant for geophysical processes such as magma, water, and gases. Predicting flow through conduits is challenging when the conduit geometry coevolves with the flow. We theoretically show that the permeability (k) of a conduit whose walls are eroding due to fast phase change increases linearly with time because of a self-reinforcing mechanism. This simple result is surprising given complex feedbacks between flow, transport, and phase change. The theory is congruent with previous experimental observations of fracture dissolution in calcite. Supporting computational fracture dissolution experiments showed that k only slightly increases until the dissolution front reaches the narrowest conduit constriction, after which the linear evolution of k manifests. Finally, the theory holds across multiple scales and a broad range of Peclet and Damkohler numbers and thus advances the prediction of dynamic mass fluxes through expanding conduits in various geologic and environmental settings
Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community-managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally-managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responses to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. In conclusion, continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.
Abstract Materials acceleration platforms (MAPs) operate on the paradigm of integrating combinatorial synthesis, high‐throughput characterization, automatic analysis, and machine learning. Within a MAP, one or multiple autonomous feedback loops may aim to optimize materials for certain functional properties or to generate new insights. The scope of a given experiment campaign is defined by the range of experiment and analysis actions that are integrated into the experiment framework. Herein, the authors present a method for integrating many actions within a hierarchical experimental laboratory automation and orchestration (HELAO) framework. They demonstrate the capability of orchestrating distributed research instruments that can incorporate data from experiments, simulations, and databases. HELAO interfaces laboratory hardware and software distributed across several computers and operating systems for executing experiments, data analysis, provenance tracking, and autonomous planning. Parallelization is an effective approach for accelerating knowledge generation provided that multiple instruments can be effectively coordinated, which the authors demonstrate with parallel electrochemistry experiments orchestrated by HELAO. Efficient implementation of autonomous research strategies requires device sharing, asynchronous multithreading, and full integration of data management in experimental orchestration, which to the best of the authors’ knowledge, is demonstrated for the first time herein.
In recent years, wildfires in the western United States have occurred with increasing frequency and scale. Climate change scenarios in California predict prolonged periods of droughts with even greater potential for conditions amenable to wildfires. The Sierra Nevada Mountains provide 70% of water resources in California, yet how wildfires will impact watershed-scale hydrology is highly uncertain. In this work, we assess the impacts of wildfires perturbations on watershed hydrodynamics using a physically based integrated hydrologic model in a high-performance-computing framework. A representative Californian watershed, the Cosumnes River, is used to demonstrate how postwildfire conditions impact the water and energy balance. Results from the high-resolution model show counterintuitive feedbacks that occur following a wildfire and allow us to identify the regions most sensitive to wildfires conditions, as well as the hydrologic processes that are most affected. For example, whereas evapotranspiration generally decreases in the postfire simulations, some regions experience an increase due to changes in surface water run-off patterns in and near burn scars. Postfire conditions also yield greater winter snowpack and subsequently greater summer run-off as well as groundwater storage in the postfire simulations. Finally, comparisons between dry and wet water years show that climate is the main factor controlling the timing at which some hydrologic processes occur (such as snow accumulation) whereas postwildfire changes to other metrics (such as streamflow) show seasonally dependent impacts primarily due to the timing of snowmelt, illustrative of the integrative nature of hydrologic processes across the Sierra Nevada-Central Valley interface.
Weather persistence from month to month is an important source of predictability on the intraseasonal time-scale. Persistence in the lower troposphere is thought to be mainly due to dynamical feedbacks between the atmosphere and physical variables at or below the surface. Many recent improvements of dynamical seasonal forecasting models have been due to better initialisations and representations of the lower boundary. While many physical mechanisms that mediate persistence are well-understood, they have not previously been considered simultaneously in a causal framework. Here we use linear methods that are widely used in the field of causal inference in statistics to identify mediators between persistent near-surface temperature anomalies from one month to the next. The variables considered are soil temperature and soil moisture at four levels, and snow depth. In Northern Europe, the high persistence of temperature in summer is shown to be mediated mainly by soil temperature anomalies. The high persistence in winter is mediated by snow depth and soil moisture in addition to soil temperature. The annual cycles of persistence are also investigated for the mid- and high latitudes of the Northern Hemisphere, confirming the important role of soil temperature in summer. Snow depth is an important mediator when, and where, its interannual variability is large: in winter at midlatitudes and in spring and autumn at high latitudes. The novel contribution of this study is the introduction of a linear causal methodology and a holistic approach that allows quantification and comparison of the different roles of soil variables and snow depth in mediating near-surface temperature persistence.