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Total and restricted energy loss rates were calculated for magnetic monopoles of charge g = 137 e in Lexan polycarbonate. Range-energy curves are also presented. The restricted energy loss model is used to estimate the appearance of a monopole track in plastic detectors. These results should be useful for the design and analysis of monopole experiments.
Total and restricted energy loss rates are calculated for magnetic monopoles of charge g = 137 e in Lexan polycarbonate. Range-energy curves are also presented. The restricted-energy-loss model is used to estimate the appearance of a monopole track in plastic detectors. The results are applied to the event observed by Price et al. and identified by them as a monopole. It is found that the observed etch rate is consistent with what one would expect for a slow magnetic monopole. These results should also be of use to other investigators for both the design and analysis of monopole experiments.
We examine the various mechanisms which have been proposed to compensate for the climatic effects of a 30% increase in the solar luminosity over the past 4 1/2 billion years. Although atmospheric greenhouse effects have received most attention, other mechanisms may have played a role of comparable importance. In particular, we note that the development of continents during the past 2 1/2 billion years could have had a significant secular effect on the atmosphere-ocean heat transport system. As a result, past climates may have been less susceptible to complete freeze-over. A simple energy balance model is used to demonstrate the magnitude of this effect. Because the CO2 greenhouse effect is not the only means of compensating for solar evolution, the faint-young-sun problem should not be used to infer past levels of atmospheric CO2.
The third phase of research will focus on the propagation and energy extraction of the pump and SERS beams in a variety of configurations including oscillator structures. In order to address these questions a numerical code capable of allowing for saturation and full transverse beam evolution is required. The method proposed is based on a discretized propagation energy extraction model which uses a Kirchoff integral propagator coupled to the three level Raman model already developed. The model will have the resolution required by diffraction limits and will use the previous density matrix results in the adiabatic following limit. Owing to its large computational requirements, such a code must be implemented on a vector array processor. One code on the Cyber is being tested by using previously understood two-level laser models as guidelines for interpreting the results. Two tests were implemented: the evolution of modes in a passive resonator and the evolution of a stable state of the adiabatically eliminated laser equations. These results show mode shapes and diffraction losses for the first case and relaxation oscillations for the second one. Finally, in order to clarify the computing methodology used to exploit the speed of the Cyber's computational speed, the time it takes to perform both of the computations previously mentioned to run on the Cyber and VAX 730 must be measured. Also included is a short description of the current laser model (CAVITY.FOR) and a flow chart of the test computations.
Stars are presented which have characteristics similar to Vega and other main-sequence stars with cool dust disks, based on the IRAS Point Source Catalog fluxes. The objects are selected to have a 60-micron/100-micron ratio similar to Vega, Beta Pic, Alpha PsA, and Epsilon Eri, and they are also required to show evidence of extension in the IRAS Working Survey Database. The fluxes are modeled using a blackbody energy distribution. The temperatures derived range from 50 to 650 K. The diameters of the dust disks observed by IRAS are estimated.
Consideration is given to the injection and interplanetary propagation of low-energy protons caused by the solar particle event of July 20, 1981, in which flare protons in the range from 35 keV to 20 MeV were observed by instruments on ISEE 3. The observed time-intensity and time-anisotropy profiles were fitted over the entire energy range using a model based on the spherically symmetric Fokker-Plank equation, including convection, diffusion, and adiabatic deceleration. The results are used to discuss the behavior of the radial interplanetary diffusion coefficient and the scattering mean free path for protons. Also, evidence is found for diffusive coronal shock acceleration of protons during the event.
An energy balance model is used to study the behavior of CO2 ice on Mars. The effect of the solar zenith angle dependence of albedo is to lengthen CO2 ice lifetimes at the poles. Hemispherical asymmetries in cloud and dust abundance could result in the survival of seasonal CO2 ice through summer in the south and not in the north, in agreement with observations. CO2 ice observed in the summertime polar cap in the south could be of recent origin, although a permanent CO2 polar cap cannot be ruled out.
Remote sensing is one of a suite of geospatial technologies that are having a growing impact in a wide variety of areas from commerce to science to public policy. The field of remote sensing evolved from the interpretation of aerial photographs to the analysis of satellite imagery, and from local area studies to global analyses, with advances in sensor system technologies and digital computing. Today remote sensor systems can provide data from energy emitted, reflected, and/or transmitted from all parts of the electromagnetic spectrum. Examples of applications of these data include population and demography studies, study of archaeological sites, energy studies using hydrological models, urban planning, environmental monitoring, environments, treaty enforcement, land use/land cover planning, weather forecasting, and agricultural production estimation, just to name a few. The material that follows provides a brief overview of the historical development of remote sensing, emphasizing the increasing complexity of platforms, systems, and tasks.
We present the first spatially resolved polarized scattered light H-band detection of the DoAr 28 transitional disk. Our two epochs of imagery detect the scattered light disk from our effective inner working angle of 0 double prime.10 (13 AU) out to 0double prime.50 (65 AU). This inner working angle is interior to the location of the system's gap inferred by previous studies using spectral energy distribution modeling (15 AU). We detected a candidate point source companion 1 double prime.08 northwest of the system; however, our second epoch of imagery strongly suggests that this object is a background star. We constructed a grid of Monte Carlo Radiative Transfer models of the system, and our best fit models utilize a modestly inclined (50 degrees), 0.01 solar mass disk that has a partially depleted inner gap from the dust sublimation radius out to approximately 8 AU. Subtracting this best fit, axi-symmetric model from our polarized intensity data reveals evidence for two small asymmetries in the disk, which could be attributable to a variety of mechanisms.
We examine and quantify how hybrid (e.g., UV+IR) star formation rate (SFR) estimators and the AFUV–β relation depend on inclination for disk-dominated galaxies using spectral energy distribution modeling that utilizes the inclination-dependent attenuation curves described in Doore et al. We perform this analysis on a sample of 133 disk-dominated galaxies from the CANDELS fields and 18 disk galaxies from the Spitzer Infrared Nearby Galaxies Survey and Key Insights on Nearby Galaxies: A Far-Infrared Survey with Herschel samples. We find that both the hybrid SFR estimators and the AFUV–β relation present clear dependencies on inclination. To quantify this dependence in the hybrid SFR estimators, we derive an inclination and a far-UV–near-IR color-dependent parametric relation for converting observed UV and IR luminosities into SFRs. For the AFUV–β relation, we introduce an inclination-dependent component that accounts for the majority of the inclination dependence with the scatter of the relation increasing with inclination. We then compare both of these inclination-dependent relations to similar inclination-independent relations found in the literature. From this comparison, we find that the UV+IR correction factor and AFUV for our hybrid and AFUV–β relations, respectively, result in a reduction in the residual scatter of our sample by approximately a factor of 2. Therefore, we demonstrate that inclination must be considered in hybrid SFR estimators and the AFUV–β relation to produce more accurate SFR estimates in disk-dominated galaxies.
The mission of NECCES is to develop an understanding of how key electrode reactions occur in cathode materials for Li based batteries, and how they can be controlled to improve electrochemical performance, from the atomistic level to the macroscopic level through the life-time of the operating battery. This mission will allow the determination of the ultimate limits of intercalation reactions for chemical energy storage. The approach and specific research goals of NECCES are to: 1. Attain reversible multi-electron transfer in a cathode material using lithium, using the model compound ε -VOPO 4 ; 2. Close the gap between the theoretical and practical energy density for intercalation compounds, using the model compound LiNi 0.85 Co 0 .10Al 0.05 O 2 ; 3. Understand the transition from cation redox to anion redox electrochemistry; 4. Understand performance limiting transport in positive electrode structures from the local through the meso to the macroscale.
This paper presents a framework that expands the URBANopt(TM) modeling platform to include 3D-printed concrete wall assemblies and assess energy efficiency and backup power trade-offs in new housing developments. Applied to a planned mixed-use neighborhood in Oil City, Pennsylvania, the workflow integrates building energy and distributed energy resource (DER) modeling to evaluate envelope and equipment upgrades alongside DER operations. Results show that advanced 3D-printed envelopes combined with efficient systems and onsite photovoltaics (PV) and storage reduce energy use intensity and sustain critical loads during outages. The framework supports planning for emerging construction technologies by quantifying key trade-offs between energy efficiency and backup power performance.
Abstract. The Energy Exascale Earth System Model (E3SM) Land Model (ELM) is a state-of-the-art land surface model that simulates the intricate interactions between the terrestrial land surface and other components of the Earth system. Originating from the Community Land Model (CLM) version 4.5, ELM has been under active development, with added new features and functionality, including plant hydraulics, radiation–topography interaction, subsurface multiphase flow, and more explicit land use and management practices. This study integrates ELM v2.1 with the Weather Research and Forecasting (WRF; WRF-ELM) model through a modified Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) framework, enabling affordable high-resolution regional modeling by leveraging ELM's innovative features alongside WRF's diverse atmospheric parameterization options. This framework includes a top-level driver for variable communication between WRF and ELM and Earth System Modeling Framework (ESMF) caps for the WRF atmospheric component and ELM workflow control, encompassing initialization, execution, and finalization. Importantly, this LILAC–ESMF framework demonstrates a more modular approach compared to previous coupling efforts between WRF and land surface models. It maintains the integrity of ELM's source code structure and facilitates the transfer of future developments in ELM to WRF-ELM. To test the ability of the coupled model to capture land–atmosphere interactions over regions with a variety of land uses and land covers, we conducted high-resolution (4 km) WRF-ELM ensemble simulations over the Great Lakes region (GLR) in the summer of 2018 and systematically compared the results against observations, reanalysis data, and WRF-CTSM (WRF coupled with the Community Terrestrial Systems Model). In general, the coupled WRF-ELM model has reasonably captured the spatial distribution of surface state variables and fluxes across the GLR, particularly over the natural vegetation areas. The evaluation results provide a baseline reference for further improvements in ELM in the regional application of high-resolution weather and climate predictions. Our work serves as an example to the model development community for expanding an advanced land surface model's capability to represent fully-coupled land–atmosphere interactions at fine spatial scales. The development and release of WRF-ELM marks a significant advancement for the ELM user community, providing opportunities for fine-scale regional representation, parameter calibration in coupled mode, and examination of new schemes with atmospheric feedback.
The spatial distribution of energy deposition is an important determinant in the formation of biologically significant lesions. It has been widely realized that Linear Energy Transfer (LET) being an average quantity is not sufficient to describe the situation at a submicroscopic scale. To remedy this to some extent 'energy-cut-off' values are sometimes used but since they are related to secondary electron energy and only indirectly to their range they are also not adequate although they may be easily calculated. 'Range-restricted LET' appears to be better but its determination is usually quite involved. Xapsos (1992) suggested a semi-empirical approximation based on a modified Bethe-formula which contains a number of assumption which are difficult to verify. A simpler and easier way is to use existing beam-models which describe energy deposition around an ion's path. They all agree that the energy density (i. e., energy deposited per unit mass) decreases with the inverse square of the distance from the track center. This simple dependence can be used to determine the fraction of total LET which is deposited in a cylinder of a given radius. As an example our own beam model. Energy density depends on distance x (measured in m) from the track center according to the presented formula.
High-frequency vibroacoustic modeling is typically performed using energy-based techniques such as Statistical Energy Analysis (SEA). Energy models require an estimate of the internal damping loss factor. Unfortunately, the loss factor is difficult to estimate analytically, and experimental methods such as the power injection method can require extensive measurements over the structure of interest. This paper discusses the implications of estimating damping loss factors using the impulse response decay method (IRDM) from a limited set of response measurements. An automated procedure for implementing IRDM is described and then evaluated using data from a finite element model of a stiffened, curved panel. Estimated loss factors are compared with loss factors computed using a power injection method and a manual curve fit. The paper discusses the sensitivity of the IRDM loss factor estimates to damping of connected subsystems and the number and location of points in the measurement ensemble.
Heating, ventilation, and air-conditioning (HVAC) systems play a significant role in building energy consumption, accounting for around 50% of total energy usage. As a result, it is essential to explore ways to conserve energy and improve HVAC system efficiency. One such solution is the use of economizer controls, which can reduce cooling energy consumption by using the free-cooling effect. However, there are various types of economizer controls available, and their effectiveness may vary depending on the specific climate conditions. To investigate the cooling energy-saving potential of economizer controls, this study employs a dry-bulb temperature-based economizer control approach. The dry-bulb temperature-based control strategy uses the outdoor air temperature as an indicator of whether free cooling can be used instead of mechanical cooling. This study also introduces an artificial neural network (ANN) prediction model to optimize the control of the HVAC system, which can lead to additional cooling energy savings. To develop the ANN prediction model, the EnergyPlus program is used for simulation modeling, and the Python programming language is employed for model development. The results show that implementing a temperature-based economizer control strategy can lead to a reduction of 7.6% in annual cooling energy consumption. Moreover, by employing an ANN-based optimal control of discharge air temperature in air-handling units, an additional 22.1% of cooling energy savings can be achieved. In conclusion, the findings of this study demonstrate that the implementation of economizer controls, especially the dry-bulb temperature-based approach, can be an effective strategy for reducing cooling energy consumption in HVAC systems. Additionally, using ANN prediction models to optimize HVAC system controls can further increase energy savings, resulting in improved energy efficiency and reduced operating costs.
Excitation of D-line radiation in collisions of Na atoms with vibrationally excited N2, H2 and D2 was studied in two modulated crossed beam experiments. In both experiments, the vibrational excitation of the molecules was provided by heating the molecular beam source to temperatures in the range of 2000 to 3000 K, which was assumed to give populations according to the Boltzmann expression. In the first experiment, a total rate coefficient was measured as a function of molecular beam temperature, with absolute calibration of the photon detector being made using the black body radiation from the heated molecular beam source. Since heating affects both the internal energy and the collisional kinetic energy, the first experiment could not determine the relative contributions of internal energy transfer versus collisional excitation. The second experiment achieved partial separation of internal versus kinetic energy transfer effects by using a velocity-selected molecular beam. Using two simple models for the kinetic energy dependence of the transfer cross section for a given change in vibrational quantum number, the data from both experiments were used to determine parameters in the models.
Equation of state (EOS) data provide necessary information for accurate multiphysics modeling, which is necessary for fields such as inertial confinement fusion. Here, we suggest a neural network surrogate model of energy and entropy and use thermodynamic relationships to derive other necessary thermodynamic EOS quantities. We incorporate phase information into the model by training a phase classifier and using phase-specific regression models, which improves the modal prediction accuracy. Our model predicts energy values to 1% relative error and entropy to 3.5% relative error in a log-transformed space. Although sound speed predictions require further improvement, the derived pressure values are accurate within 10% relative error. Our results suggest that neural network models can effectively model EOS for inertial confinement fusion simulation applications.