Energy Map Research Articles

Energy Mapping of Additive Manufacturing Processes Using Sankey Diagrams

Energy Mapping of Additive Manufacturing Processes Using Sankey Diagrams

Characterization of hot workability of IN617B alloy using activation energy, Zener-Hollomon parameter and hot processing maps

In order to predict the hot workability of the material more accurately, this paper takes the hot deformation of IN617B as the example. The activation energy (Q) map, Zener-Hollomon parameter (Z) map, and hot processing map were established based on the hot compression tests conducted at 950–1200 °C and 0.01–5 s−1. It was found that the area with high power dissipation values (denoted by η) in the hot processing map did not match the complete dynamic recrystallization (DRX) region completely. However, the microstructure corresponding to the high η area and low Z and Q area exhibited higher DRX. Therefore, the optimal hot processing region for this alloy was determined to be 1200 °C/0.1 s−1/0.8. Under this parameter, the DRX mechanism of IN617B alloy was dominated by discontinuous dynamic recrystallization (DDRX), supplemented by small amounts of continuous dynamic recrystallization (CDRX) and twinning dynamic recrystallization (TDRX).

Deciphering the Influence of Ground-State Distributions on the Calculation of Photolysis Observables.

Nonadiabatic molecular dynamics offers a powerful tool for studying the photochemistry of molecular systems. Key to any nonadiabatic molecular dynamics simulation is the definition of its initial conditions (ICs), ideally representing the initial molecular quantum state of the system of interest. In this work, we provide a detailed analysis of how ICs may influence the calculation of experimental observables by focusing on the photochemistry of methylhydroperoxide (MHP), the simplest and most abundant organic peroxide in our atmosphere. We investigate the outcome of trajectory surface hopping simulations for distinct sets of ICs sampled from different approximate quantum distributions, namely harmonic Wigner functions and ab initio molecular dynamics using a quantum thermostat (QT). Calculating photoabsorption cross-sections, quantum yields, and translational kinetic energy maps from the results of these simulations reveals the significant effect of the ICs, in particular when low-frequency (∼ a few hundred cm-1) normal modes are connected to the photophysics of the molecule. Overall, our results indicate that sampling ICs from ab initio molecular dynamics using a QT is preferable for flexible molecules with photoactive low-frequency modes. From a photochemical perspective, our nonadiabatic dynamics simulations offer an explanation for a low-energy tail observed at high excitation energy in the translational kinetic energy map of MHP.

Binding of viral nuclear localization signal peptides to importin-α nuclear transport protein

Using all-atom replica-exchange molecular dynamics simulations, we mapped the mechanisms of binding of the nuclear localization signal (NLS) sequence from Venezuelan equine encephalitis virus (VEEV) capsid protein to importin-α (impα) transport protein. Our objective was to identify the VEEV NLS sequence fragment that confers native, experimentally resolved binding to impα as well as to study associated binding energetics and conformational ensembles. The two selected VEEV NLS peptide fragments, KKPK and KKPKKE, show strikingly different binding mechanisms. The minNLS peptide KKPK binds non-natively and nonspecifically by adopting five diverse conformational clusters with low similarity to the x-ray structure 3VE6 of NLS-impα complex. Despite the prevalence of non-native interactions, the minNLS peptide still largely binds to the impα major NLS binding site. In contrast, the coreNLS peptide KKPKKE binds specifically and natively, adopting a largely homogeneous binding ensemble with a dominant, highly native-like conformational cluster. The coreNLS peptide retains most of native binding interactions, including π-cation contacts and a tryptophan cage. While KKPK binding is governed by a complex multistate free energy landscape featuring transitions between multiple binding poses, the coreNLS peptide free energy map is simple, exhibiting a single dominant native-like bound basin. We argue that the origin of the coreNLS peptide binding specificity is several electrostatic interactions formed by the two C-terminal amino acids, Lys10 and Glu11, with impα. The coreNLS sequence is then sufficient for native binding, but none of the amino acids flanking minNLS, including Lys10 and Glu11, are strictly necessary for the native pose. Our analyses indicate that the VEEV coreNLS sequence is virtually unique among human and viral proteins interacting with impα making it a potential target for VEEV-specific inhibitors.

Turbulent wave-balance exchanges in the ocean

Oceanic flows are turbulent and multi-scale in nature, and are composed of fast internal waves and slowly evolving balanced eddies. Contrary to conventional wisdom in physical oceanography, the past two decades ofin situ, satellite altimeter and realistically forced global scale ocean model outputs have revealed that internal gravity waves can have comparable or higher energy levels than geostrophically balanced flows at 10–100 km scales in different parts of the world’s oceans. These relatively recent findings have fuelled a wide range of research activities aimed at understanding how fast internal gravity waves interact with slowly evolving balanced flows, particularly with the goal of deducing whether internal waves can form an energy sink for oceanic balanced flows. In this paper, we comprehensively review theoretical, numerical and observational investigations undertaken to study internal wave-balance flow exchanges. Theoretical calculations, inspired by different wave-balance regimes seen in observational and global ocean model outputs, are used to point out that internal waves can affect balanced flow dynamics. The theoretical results are followed up by a detailed discussion of numerical results on wave-balance interactions in a broad set of parameter regimes. The numerical results reveal how different kinds of waves exchange energy with balance flow, affect energy flux across scales of balanced flow and facilitate the generation of small-scale dissipative balanced flow structures. The numerical simulation results and global internal wave energy and balanced energy maps are used to conjecture that out of the 0.8 TW of power going to balanced flow kinetic energy in the ocean, at least 0.1 TW could be dissipated by internal gravity waves. We therefore hypothesize that internal waves can form a non-negligible energy sink for balanced flow in the world’s oceans.

Hot deformation behavior of 309L stainless steel

Hot compression tests were carried out on 309 L austenitic stainless steel at different deformation temperatures (900–1100 ℃) and different strain rates (0.01–10 s−1). Based on the stress-strain curve, three constitutive models, Modified Johnson-Cook, Modified Zerilli–Armstrong and Strain Compensation Arrhenius, are constructed, and it is found that the Strain Compensation Arrhenius model has the highest accuracy. Besides, the Arrhenius model and the dynamic material model were adopted to construct the activation energy map and power dissipation map of 309 L stainless steel with different strains. In the region with high temperatures and high strain rates, low activation energy Q value and high power dissipation η value were shown. According to the microstructure, the deformation of ferrite and austenite phases was uniform at 1050 and 1100 ℃/10 s−1, the level of recrystallization fraction was high, and the grains were fine and uniform. However, at 900 ℃/10 s−1, the microstructure suffered serious distortion, the ferrite was significantly elongated, and cracking occurred at the phase boundaries. A conceptual processing map was built through the prediction of activation energy map, power dissipation map and analysis of microstructure in combination. The optimal hot working range was 1025–1100 ℃/2.7–10 s−1, and the instability region was 900–958 ℃/0.28–10 s−1.

High-k/InGaAs interface defects at cryogenic temperature

Oxide defects in the high-k/InGaAs MOS system are investigated. The behaviour of these traps is explored from room temperature down to 10 K. This study reveals that the exchange of free carriers between oxide states and either the conduction or the valence band is strongly temperature dependant. The capture and emission of electrons is strongly suppressed at 10 K as demonstrated by the collapse of the capacitance frequency dispersion in accumulation for n-InGaAs MOS devices, though hysteresis in the C-V sweeps is still present at 10 K. Phonon assisted tunnelling processes are considered in the simulation of electrical characteristics. The simulated data match very well the experimental characteristics and provide energy and spatial mapping of oxide defects. The multi phonon theory also help explain the impedance data temperature dependence. This study also reveals an asymmetry in the free carrier trapping between n and p type devices, where hole trapping is more significant at 10 K.

Integrating heat pumps into district heating systems: A multi-criteria decision analysis framework incorporating heat density and renewable energy mapping

The implementation of district heating (DH) projects necessitates a thorough and accurate evaluation and planning process. The availability of energy resources is often the key determinant in identifying the suitability of a specific location for district heating applications. Also, it is crucial to consider the other factors during the planning stage: the environment, economics, and technical parameters. This research aims to plan and implement a DH site selection model based on a geographic information system (GIS). This model employs Boolean and fuzzy toolboxes to analyze various layers, followed by the analytic hierarchy process (AHP) to identify the most appropriate locations for district heating in Gaziantep, Turkey. A mixed integer linear programming (MILP) approach is utilized to model proposed energy systems to achieve optimal operation and planning. The study's primary objective is to minimize the levelized cost of energy (LCOE), which encompasses initial costs, operations, maintenance, replacement expenses, and energy demand while also meeting the energy demand. A hybrid energy system that includes solar thermal/photovoltaic (ST, PV) energy, wind turbine (WT), and heat pump (HP) is considered, and its LCOE of optimal size is compared to other scenarios using HOMER simulation software. The results indicate that 270 km2 of the study area is suitable for DH implementation, with 83 km2 being highly suitable. Among the various scenarios, the hybrid energy system with a renewable energy penetration rate of approximately 78% achieves the best LCOE of 0.0442. The study concludes by providing a map of the potential for district heating and a discussion of the strengths and drawbacks of each scenario.

Control of electronic structure in (Cu, Ag)(Ga, In)Se2 for high efficiency solar cells

A three-dimensional (3D) band-gap energy (E g) map was constructed for a (Cu1−y Ag y )(Ga x In1−x )Se2 (CAGISe) system. This system’s E g increases monotonically from CuInSe2 (CISe) as the ratios of both Ga/(Ga+In) [GGI], x, and Ag/(Cu+Ag) [ACA], y, increase. Furthermore, the energy levels of the VB maximum (VBM) and the conduction band minimum (CBM) were also mapped in 3D. In this CAGISe system, there is no significant change in VBM, whereas CBM does show an increase as the GGI ratio increases. However, as the ACA ratio increases, there is a decrease in VBM level but no significant change in CBM. The substitution effects of Ga for In and Ag for Cu in CISe are discussed on the basis of “principles of orbital interaction.”

On harmonic and biharmonic maps from gradient Ricci solitons

AbstractWe study harmonic and biharmonic maps from gradient Ricci solitons. We derive a number of analytic and geometric conditions under which harmonic maps are constant and which force biharmonic maps to be harmonic. In particular, we show that biharmonic maps of finite energy from the two‐dimensional cigar soliton must be harmonic.

Density Function Theory Study of the Physicochemical Characteristics of 2-nitrophenol

2-Nitrophenol (2-NP) is utilized in the production of bio-refractory organic compounds, and petrochemicals, and in the synthesis of many drugs and weed killers. The chemical structure of 2-NP is C6H5NO3. The structure of 2-NP is important as the nitro group (NO2. In this present investigation, the Gaussian 5.0 program was used to compute the difference in energy level that exists between the HOMO and LUMO states of the BGs.This information was then used to optimize the shape of the 2-NP structures using DFT methods. The 3-21G/B3LYP base set has a minimum value for the BG energy of 3.48 eV. This is the minimum value that can be achieved. The DOS for 2-NP was measured to have its maximum possible value of 2.23 ev/atom. According to the results of the IR, and Raman spectrum, the C-H stretching vibration peak for 2-NP was found to be between 3208.96 cm-1 and 3243.76 cm-1. The maximum excitation energy was analyzed at a wavelength of 382.1 nm, and the oscillator strength was determined at 0.0537 UV Spectroscopy. In the potential energy map (PE), the colors are changed from blue to red in the range of -4.442e-2 to 4.442e-2.

NiO nanoparticles, an algorithm of their biosynthesis, toxicity, and biomedical activities

The green synthesis of metal oxide nanoparticles is interestingly becoming familiar as the reason of its non-toxicity, economical, eco-friendly, and commerciality. The secondary metabolites and bioactive molecules in biomaterial extract play an important role of reducing, capping, stabilizing and chelating activities to form the nanoparticles as a substitute of hazardous chemical surfactants. Hence this present work concentrated on the biogenic synthesis of NiO nanoparticles using grains extract of Oryza longistaminata (red rice), and their toxicity assessment as well as biomedical applications. The synthesized nanoparticles were widely characterized by using several analytical and biomedical techniques. The reduction mechanism of Ni2+ ions using major active phytocompound in red rice grains extract was stated. UV–visible spectroscopic analysis revealed the formation of NiO nanoparticles by emerging the sharp surface Plasmon resonance band at 326 nm. The absorption peaks of red rice grains extract at 206, 260, 330 and 410 nm stated the presence of phytocompounds in them. X-ray diffraction pattern explicated the high crystallinity of NiO nanoparticles and their average crystallite size was found to be at 36 nm. The diffraction pattern of red rice grains revealed the amorphous characteristic. Fourier transform infrared analysis displayed the different vibrational functional groups of nanoparticles and red rice grains. Dynamic light scattering analysis showed the particle size distribution was in between 30-65 nm. High-resolution transmission electron microscopic analysis showed the hexagonal, rectangular, oval and spherical shaped polymorphism of NiO nanoparticles and their size was in 25-50 nm. Energy dispersive X-ray spectrum and mapping analyses validated the formation of NiO nanoparticles by the major existence of Ni and O elements. The high toxicity of nanoparticles towards MG-63 osteosarcoma cancer cells was revealed at 94.69% in 100 μg/mL concentration. The nanoparticles showed no severe toxicity against HEK293 normal cells and red blood cells till higher concentration. The biomedical analyses such as antioxidant, anti-inflammatory and anti-diabetic activities exposed the potential bio-drug activity of NiO nanoparticles with maximum activity of 86.22, 84.23 and 85.18% in the high concentration of 80 μg/mL. The antibacterial activity divulged the good bactericidal drug nature of NiO nanoparticles against both Gram-positive (S. aureus and B. Subtilis) and Gram-negative (S. typhi and K. pneumonia) bacteria with low MBC/MIC ratio. As per the assessment of results, the biosynthesized NiO nanoparticles have non-carcinogenic, high biocompatible and potent nature and it suggests that they can be used as therapeutic candidates in biomedical, clinical and pharmaceutical fields for treating various diseases.

Automatic Optimization of Multi-Well Multi-Stage Fracturing Treatments Combining Geomechanical Simulation, Reservoir Simulation and Intelligent Algorithm

Shale reserves have become an ever-increasing component of the world’s energy map. The optimal design of multi-well multi-stage fracturing (MMF) treatments is essential to the economic development of such resources. However, optimizing MMF treatments is a complex process. It requires geomechanical simulation, reservoir simulation, and automatic optimization. In this work, an integrated workflow is proposed to optimize MMF treatments in an unconventional reservoir, and the net present value (NPV) of reserves was treated as the objective function. The forward model consists of two submodels: a hydraulic fracturing model and a reservoir simulation model. The stochastic simplex approximation gradient (StoSAG) is used with the steepest ascent algorithm to maximize the NPV function. The computational results show that optimizing the fracture design can achieve a 20% higher NPV than that obtained with the field reference case. The drainage area of the optimal design is larger than that of the initial design. The maximum gas production rate increases from 23.75 MMSCF/day to 34.43 MMSCF/day and the maximum oil production rate increases from 497 STB/day to 692 STB/day. Therefore, new optimization paths can accelerate fracture design and help increase well production. This paper innovatively proposes a coupled workflow that can reduce the waste of manpower and improve the optimization results.

Acquisition of microscopic and local stress-strain curves by combination of HR-EBSD and DIC methods

A method for obtaining microscopic and localized stress-strain curves is proposed by combining strain measurements using the digital image correlation (DIC) method with stress measurements using high-resolution electron backscattered diffraction (HR-EBSD). A dataset containing 11 steps of stress–strain information in a single subset was created by applying georeferencing to DIC strain maps and HR-EBSD stress maps measured in a deformation-interrupted microstructure. This analysis allowed us to obtain local stress-strain curves and strain energy maps of polycrystalline nickel alloys. A comparison of the stress-strain curves obtained from any subset in the map revealed that these curves show extremely diverse shapes depending on the location in the microstructure.

High-accuracy lunar global brightness-temperature mapping using third-order Fourier fitting and co-kriging interpolation

The use of microwave radiation data collected by lunar orbiters to infer the lunar brightness-temperature (TB) distribution is of great importance to lunar scientific exploration. The TB data acquired by China's Chang'E-2 passive microwave radiometer (MRM) is one of the basic materials for lunar temperature mapping. Core issues of lunar microwave TB mapping include data fitting at different latitudes, outlier removal, and integrated spatial interpolation considering influencing factors. We applied a third-order Fourier function to fit the lunar TB data, which effectively removes outliers considering the fitting characteristic and three-sigma rule (FCTSR). Because the lunar surface temperature is influenced by a variety of factors such as topography and albedo, we then built a multi-factor co-kriging interpolation method to perform lunar TB mapping accurately. The cross-validation shows that, in terms of the mean-absolute-error and root-mean-square-error, the multi-factor co-kriging interpolation improves the mapping accuracy by 30%–60% compared to inverse distance interpolation and ordinary kriging interpolation. The analysis shows that topography and albedo are the most important factors influencing the lunar TB, and the TB maps at 37 GHz reveal cold spots that can be considered as younger craters. It is concluded that the proposed data fitting, denoising and spatial interpolation methods significantly improve the lunar TB mapping. The results and scientific data can also provide a basic energy map for lunar roving path planning and subsequent lunar exploration.

Characterization of bioenergetic and kinematic plasticity of bovine sperm reveals novel and dynamic temporal traits.

Sperm transport through the female reproductive tract requires energy for motility and fertilization. Sperm kinematic assessment is conducted as an industry standard to estimate semen quality prior to bovine insemination. However, individual samples with similar post-thaw motility result in different pregnancy outcomes, suggesting that differences in bioenergetics may be important for sperm function. Thus, characterization of bioenergetic and kinematic parameters of sperm over time may reveal novel metabolic requirements for sperm function. Post-thawed sperm from five samples of individual (A, B, C) and pooled bulls (AB, AC) were assessed at 0 and 24 hr after thawing. Sperm were evaluated for kinematics via Computer-Assisted Sperm Analyses and bioenergetic profiles using a Seahorse Analyzer for basal respiration [BR], mitochondrial stress test [MST] and energy map [EM]. Motility was nearly identical among samples after thawing and no differences in bioenergetics were detected. However, after 24 hr of sperm storage, pooled sperm samples (AC) presented with higher BR and proton leakage compared to other samples. Sperm kinematic variability among samples was higher after 24 hr, suggesting difference in sperm quality may manifest over time. Despite a reduction in motility and mitochondrial membrane potential, BR was higher at 24 hr compared to 0 hr for nearly all samples. A metabolic divergence between samples was detected by EM, indicating a shift in bioenergetic profiles over time that was undetected after thawing. These new bioenergetic profiles elucidate a novel dynamic plasticity of sperm metabolism over time while suggesting an influence of heterospermic interactions for further investigation.

Optimal Configuration of Hybrid Energy Storage Capacity in a Microgrid Based on Variational Mode Decomposition

The capacity configuration of the energy storage system plays a crucial role in enhancing the reliability of the power supply, power quality, and renewable energy utilization in microgrids. Based on variational mode decomposition (VMD), a capacity optimization configuration model for a hybrid energy storage system (HESS) consisting of batteries and supercapacitors is established to achieve the optimal configuration of energy storage capacity in wind–solar complementary islanded microgrids. Firstly, based on the energy mapping relationship between the frequency domain and time domain, the decomposition mode number K of VMD is determined based on the principle of minimum total mode aliasing energy. Then, considering the smoothing fluctuation characteristics of different energy storage components, the dividing point N of high frequency and low frequency in the unbalanced power between the source and load in the microgrid is selected to allocate charging and discharging power instructions for the battery and supercapacitor. Finally, taking the annual comprehensive cost of the HESS as the objective function, a hybrid energy storage capacity optimization configuration model is established, and the dividing point N is used as the optimization variable to solve the model in order to obtain the optimal configuration results. The case study results show that the proposed method is more economical and feasible than the existing energy storage configuration methods.

Simulation of Explosion Crater of Earth Penetrating Nuclear Bomb Based on Equivalency to TNT Mass


 
 
 The structure size of the crater formed by the earth-penetrating nuclear bomb explosion is one of the important parameters for evaluating the earth-penetrating nuclear bomb damage power. Obtaining the structure size of the crater formed by the earth-penetrating nuclear bomb explosion with different yields is great significance for the evaluation and design of the nuclear bomb damage power. In this study, considering the contradictory relationship between the structure size of the earth-penetrating nuclear bomb and the structure size of the equivalent TNT mass, we propose to use the equivalent energy mapping method to realize the finite element numerical simulation of the earth-penetrating nuclear bomb exploding into craters analyzed and compared the simulation results with the structure size of the crater formed by the ESS nuclear bomb explosion in the United States. The analysis results show that the error between the simulated crater radius and the real crater radius is 3.26%, and the error between the simulated crater depth and the real crater depth is 28.57 %. It meets the calculation accuracy error range of crater formation from nuclear explosion to chemical explosion. Therefore, this method provides an effective numerical simulation method and a means of obtaining the structural size data of the explosion crater for the earth-penetrating nuclear bomb cratering.
 
 

On the Challenges of Acoustic Energy Mapping Using a WASN: Synchronization and Audio Capture

Acoustic energy mapping provides the functionality to obtain characteristics of acoustic sources, as: presence, localization, type and trajectory of sound sources. Several beamforming-based techniques can be used for this purpose. However, they rely on the difference of arrival times of the signal at each capture node (or microphone), so it is of major importance to have synchronized multi-channel recordings. A Wireless Acoustic Sensor Network (WASN) can be very practical to install when used for mapping the acoustic energy of a given acoustic environment. However, they are known for having low synchronization between the recordings from each node. The objective of this paper is to characterize the impact of current popular synchronization methodologies as part of the WASN to capture reliable data to be used for acoustic energy mapping. The two evaluated synchronization protocols are: Network Time Protocol (NTP) y Precision Time Protocol (PTP). Additionally, three different audio capture methodologies were proposed for the WASN to capture the acoustic signal: two of them, recording the data locally and one sending the data through a local wireless network. As a real-life evaluation scenario, a WASN was built using nodes conformed by a Raspberry Pi 4B+ with a single MEMS microphone. Experimental results demonstrate that the most reliable methodology is using the PTP synchronization protocol and audio recording locally.

Saliency prediction based on multi-channel models of visual processing

Visual attention is one of the most significant characteristics for selecting and understanding the outside redundancy world. The human vision system cannot process all information simultaneously due to the visual information bottleneck. In order to reduce the redundant input of visual information, the human visual system mainly focuses on dominant parts of scenes. This is commonly known as visual saliency map prediction. This paper proposed a new psychophysical oriented saliency prediction architecture, which inspired by multi-channel model of visual cortex functioning in humans. The model consists of opponent color channels, wavelet transform, wavelet energy map, and contrast sensitivity function for extracting low-level image features and providing a maximum approximation to the low-level human visual system. The proposed model is evaluated using several datasets, including the MIT1003, MIT300, TORONTO, SID4VAM, and UCF Sports datasets. We also quantitatively and qualitatively compare the saliency prediction performance with that of other state-of-the-art models. Our model achieved strongly stable and better performance with different metrics on natural images, psychophysical synthetic images and dynamic videos. Additionally, we suggested that Fourier and spectral-inspired saliency prediction models outperformed other state-of-the-art non-neural network and even deep neural network models on psychophysical synthetic images. In the meantime, we suggest that deep neural networks need specific architectures and goals to be able to predict salient performance on psychophysical synthetic images better and more reliably. Finally, the proposed model could be used as a computational model of primate low-level vision system and help us understand mechanism of primate low-level vision system. The project page can be available at: https://sinodanishspain.github.io/HVS_SaliencyModel/ .