Input Fluctuations Research Articles

Hydrodynamic Modeling and Parameter Identification of a Bionic Underwater Vehicle: RobDact.

In this paper, the hydrodynamic modeling and parameter identification of the RobDact, a bionic underwater vehicle inspired by Dactylopteridae, are carried out based on computational fluid dynamics (CFD) and force measurement experiment. Firstly, the paper briefly describes the RobDact, then establishes the kinematics model and rigid body dynamics model of the RobDact according to the hydrodynamic force and moment equations. Through CFD simulations, the hydrodynamic force of the RobDact at different speeds is obtained, and then, the hydrodynamic model parameters are identified. Furthermore, the measurement platform is developed to obtain the relationship between the thrust generated by the RobDact and the input fluctuation parameters. Finally, by combining the rigid body dynamics model and the fin thrust mapping model, the hydrodynamic model of the RobDact at different motion states is constructed.

Experimental Investigation on the Dynamics of an Organic Rankine Cycle Evaporator with Large-Mass Fins for the Purpose of Reducing Heat Input Fluctuations

Experimental Investigation on the Dynamics of an Organic Rankine Cycle Evaporator with Large-Mass Fins for the Purpose of Reducing Heat Input Fluctuations

Simulation of Density and Flow Dynamics in a Lagoon Aquifer Environment and Implications for Nutrient Delivery From Land to Sea

The near coastal zone, hosting the saltwater-freshwater interface, is an important zone that nutrients from terrestrial freshwaters have to pass to reach marine environments. This zone functions as a highly reactive biogeochemical reactor, for which nutrient cycling and budget is controlled by the water circulation within and across that interface. This study addresses the seasonal variation in water circulation, salinity pattern and the temporal seawater-freshwater exchange dynamics at the saltwater-wedge. This is achieved by linking geophysical exploration and numerical modeling to hydrochemical and hydraulic head observations from a lagoon site at the west coast of Denmark. The hydrochemical data from earlier studies suggests that increased inland recharge during winter drives a saltwater-wedge regression (seaward movement) whereas low recharge during summer causes a wedge transgression. Transient variable density model simulations reproduce only the hydraulic head dynamics in response to recharge dynamics, while the salinity distribution across the saltwater wedge cannot be reproduced with accuracy. A dynamic wedge is only simulated in the shallow part of the aquifer (<5 m), while the deeper parts are rather unaffected by fluctuations in freshwater inputs. Fluctuating salinity concentrations in the lagoon cause the development of a temporary intertidal salinity cell. This leads to a reversed density pattern in the underlying aquifer and the development of a freshwater containing discharge tube, which is confined by an overlying and underlying zone of saltwater. This process can explain observed trends in the in-situ data, despite an offset in absolute concentrations. Geophysical data indicates the presence of a deeper low hydraulic conductive unit, which coincides with the stagnant parts of the simulated saltwater-wedge. Thus, exchange fluxes refreshing the deeper low permeable areas are reduced. Consequently, this study suggests a very significant seasonal water circulation within the coastal aquifer near the seawater-freshwater interface, which is governed by the hydrogeological setting and the incoming freshwater fluxes, where nutrient delivery is limited to a small corridor of the shallow part of the aquifer.

Using machine learning to evaluate the fidelity of heavy equipment acoustic simulations

Audio quality is an important consideration when creating acoustic simulations. However, there has been a longstanding tradeoff in evaluating the quality or fidelity of sound: subjective listening tests are time consuming and expensive, but objective measures often fail to capture the nuances of human perception. The research presented here seeks to address this problem by investigating the use of machine learning to evaluate the fidelity of heavy equipment acoustic simulations. The developed models are designed to classify sounds into one of two categories, based on whether the audio is “natural” sounding or “artificial” sounding. Two distinct datasets are presented. The first, made up of a library of compressed recordings of heavy equipment, is used primarily for developmental purposes. The second, made up of a library of simulated audio clips, is used to test performance for the intended purpose of evaluating simulated audio fidelity. Several common algorithms are compared and various audio features considered in developing the machine learning models. The final model consists of a logistic regression algorithm and uses the input features loudness, sharpness, roughness, fluctuation strength, and Mel-frequency cepstral coefficients. The developed models accurately predict human perceptions of audio fidelity, achieving approximately 98% accuracy for both datasets. The accuracies achieved provide evidence that machine learning models could potentially supplant listening tests, although limitations including the scope of the dataset and the small number of listening test participants necessitate further validation.

Simulation of multi-power composite electric tractor based on power fluctuation ratio

All Combined with the characteristics of frequent abrupt load in the field operation of tractors, and aiming at the problems of single motor energy input and large fluctuation of battery state in the energy system of pure electric tractors, a power supply structure with multiple battery packs was proposed. A dynamic model considering real-time power and load fluctuation and a multi-power cooperative input model based on fuzzy control threshold logic rule based on power fluctuation ratio are established. Matlab and Simulink are used to simulate the model and compare it with the traditional single power model. The results show that when the speed is constant ploughing, the output power of the lithium battery of the multi-power cooperative input model is effectively compensated compared with that of the single-power model under sudden load. The average fluctuation ratio of rising power decreases from 5.8% / s to 2.7% / s, which realizes “peak clipping” and “slow peak” when the current fluctuates greatly. and then made the estimation of battery state of charge (SOC) more accurate, and prolonged the battery life.

Empirical evidence of a fluctuation theorem for the wind mechanical power input into the ocean

Abstract. Ocean dynamics is predominantly driven by the shear stress between the atmospheric winds and ocean currents. The mechanical power input to the ocean is fluctuating in space and time and the atmospheric wind sometimes decelerates the ocean currents. Building on 24 years of global satellite observations, the input of mechanical power to the ocean is analysed. A fluctuation theorem (FT) holds when the logarithm of the ratio between the occurrence of positive and negative events, of a certain magnitude of the power input, is a linear function of this magnitude and the averaging period. The flux of mechanical power to the ocean shows evidence of a FT for regions within the recirculation area of the subtropical gyre but not over extensions of western boundary currents. A FT puts a strong constraint on the temporal distribution of fluctuations of power input, connects variables obtained with different lengths of temporal averaging, guides the temporal down- and up-scaling and constrains the episodes of improbable events.

Exceptionally preserved calcified sponge assemblagesin Upper Jurassic carbonates of the eastern Getic Carbonate Platform (Southern Carpathians, Romania)

A rich poriferan assemblage was identified within the easternmost part of the Getic Carbonate Platform of Romania (Grădiștei Gorges). The excellent preservation state of most poriferans here led to the discovery of a new species (Neuropora gigantea Pleș & Schlagintweit, n. sp.) and to the identification of previously unknown diagnostic features in some species (Sarsteinia babai Schlagintweit & Gawlick, 2006 emend., Neuropora lusitanica Termier, 1985, Sphaeractinia steinmanni Canavari, 1893). Calciagglutispongia yabei Reitner, 1992, Sarsteinia babai and Sphaeractinia steinmanni are reported for the first time from the Upper Jurassic carbonates of the Getic Carbonate Platform. The sedimentary input fluctuations and the nutrient competition had an important role in understanding the morphological adaptations of the analysed species. The existing palaeoecological and palaeoenvironmental conditions generated different distribution patterns towards the reef profile and also preferential adaptations to a specific Tethyan domain. As opposed to the poriferan assemblages from the northern Tethyan shelves, these organisms formed sponge-coral-microencruster boundstones at the margins and fore-reefal zones of isolated carbonate platforms within the intra-Tethyan realm. The importance of calcified sponges in reef-zonation is highlighted by the establishment of a general zonation model. Three zones can be distinguished: 1) Cladocoropsis-Milleporidium zone (back-reef area); 2) Bauneia-Chaetetopsis-Parastromatopora zone (central reef area); and 3) Sphaeractinia/Ellipsactinia-Neuropora zone for the fore-reef area. In the absence of a true reef framework these calcified sponges developed typical morphologies, environmental adaptations and partnerships with other biotic groups which strongly influenced the carbonate production throughout the intra-Tethyan domain.

Roll dynamics and control enhancement of an oceanic AUV by a four-decoupled-fins system

Autonomous Underwater Vehicles (AUVs) are subjected to several induced roll-destabilizing internal/external moments. Thus, roll control is a significant issue for many researchers, designers, and engineers to define, design, or perform the desired AUV missions due to the coupled dynamics of roll and other degrees of freedom (DOFs). In this paper, the roll dynamics and control enhancement of a REMUS AUV is studied using a four-decoupled-fins (FDF) roll control system by developing a 6DOF simulator. The results show that: 1) the roll angle deflections considerably affect the other degrees of freedom due to their coupled dynamics in both open-loop and closed-loop systems; 2) In large roll angle deflections, the FDF system (70% stern and 30% rudder fins) is needed to produce sufficient minimum oscillatory roll control forces. 3) The fins incident flow has lower energies in producing the roll control forces in lower forward speeds, causing the fluctuations of actuators' inputs and trajectory paths. 4) A limited but considerable desired roll angle can be achieved at a given forward speed; the maximum value of desired roll angle is 62∘ for the desired forward speed of 4m/s.

Linear optical circuits characterization by means of thermal field correlation measurement

We present a novel technique for linear optical circuits characterization, based on thermal field correlation measurements. Unlike the other known methods for multichannel interferometers measurements, proposed technique is robust to the input and output phase fluctuations and does not require any single-photon sources and detectors. This method has been tested in a numerical experiment and has proven to be effective even in the presence of noise.

Investment Advantages of Broiler Production Using the Partnership System: A Study in Indonesia

Purpose: Broiler business with independent pattern in Minahasa Regency, North Sulawesi often experiences problems with input and output price fluctuations. Therefore, farmers try to collaborate in partnership with companies that have better capital and technology. An evaluation needs to be carried out whether partnership model of broiler businessin North Minahasa, North Sulawesi Province is financially beneficial or not.Research Method: The research was a case study performed in UD. Matuari Waya, the only broiler farming entities in District of Kalawat, Regency of North Minahasa, of which was partnered with a national-scale husbandry company, Charoen Phokpand Ltd. Data were analyzed through business feasibility scope using analysis of investment criteria and sensitivity model.Findings: Partnership model was financially beneficial to be developed further, by NPV value of IDR.1,487,877,624 (US$101,909.43), net B/C, of 1.219, internal rate of return of 63.18% and the payback period within 1 year & 7 months. Moreover, the result of sensitivity analysis shows that: if price of broiler declined about 15% and operational cost was increased of 12%, the broiler business could still be performed. Nonetheless, whereas broiler’s production declined for 10%, this partnership was non-feasible to be developed since the value of NPV was negative and net B/C was lower than 1.Research Limitations: This study was constrained by the limited broiler breeders with partnership pattern in Kalawat District as the region with the largest broiler population.Originality/Value: The results provide new information on business development standards for broiler chicken partnerships in the context of a decline in output price, decrease of broiler production and an increase in inputs price.

Process simulation and techno-economic performance evaluation of alternative technologies for biodiesel production from low value non-edible oil

In this study the techno-economic performances of three possible technologies have been assessed to identify the better one. The studied technologies include: Glycerol enriched CaO catalyzed, Supercritical ethanol, and Solid acid catalyzed processes. The overall study is based on complete process simulations using two commercially known software – Aspen Plus and Super Pro. The complete process layout for each option has been designed based on reasonable assumptions and optimum reaction conditions taken from relevant literatures. The amount and quality of biodiesel and glycerol as well as the amount of biodiesel per amount of feedstock used have been used to assess the relative technical performances among the process alternatives. For economic performance evaluation, the total cost of investment, unit cost of production, internal rate of return, net present value and project payback time have been used. The economic feasibility of each process towards change in production capacity has also been assessed. In addition, the sensitivity of each process scenario for the possible global market fluctuations of inputs and outputs has been evaluated. The glycerol enriched CaO catalyzed option is found to be the most economically feasible option under the given market scenario. All the three options are proved to be good in their technical performances, even though the solid acid catalyzed, and supercritical options are not economically efficient.

Microbial composition in different physical compartments of six constructed wetland systems in New Zealand

Microbial communities are vital for nutrient attenuation in surface-flow constructed treatment wetlands (CTWs). We used phospholipid fatty acid (PLFA) analysis to describe microbial communities in water, soil, sediment, and fresh humus compartments in six CTWs treating agricultural run-off in the Waikato Region of New Zealand. Sites ranged in their design and not all compartments could be sampled at all sites. Bacteria were the most dominant organisms in all compartments at all sites. The water compartment had less absolute abundance of all organisms, and the least relative abundance of all microbial groups except for total bacteria, at all sites. The water compartment also had a different microbial community composition than the other (more solid) compartments. Microbial communities were consistent across the 6 CTWs regardless of system design. There were more Gram-positive than Gram-negative bacteria, inferring a greater resistance and less resilience to perturbations suggesting CTW systems may not be able to respond rapidly to fluctuations in nutrient inputs due to the prevalence of K-strategist organisms. Actinomycetes were the least abundant microbial group but their role in CTWs is not clear. There were no correlations between microbial groups and compartment chemical properties. Reaching cleaner water aspirations would be facilitated by assessment of both community composition and function in CTW physical compartments.

One Way or Another: Cortical Language Areas Flexibly Adapt Processing Strategies to Perceptual And Contextual Properties of Speech.

Cortical circuits rely on the temporal regularities of speech to optimize signal parsing for sound-to-meaning mapping. Bottom-up speech analysis is accelerated by top-down predictions about upcoming words. In everyday communications, however, listeners are regularly presented with challenging input-fluctuations of speech rate or semantic content. In this study, we asked how reducing speech temporal regularity affects its processing-parsing, phonological analysis, and ability to generate context-based predictions. To ensure that spoken sentences were natural and approximated semantic constraints of spontaneous speech we built a neural network to select stimuli from large corpora. We analyzed brain activity recorded with magnetoencephalography during sentence listening using evoked responses, speech-to-brain synchronization and representational similarity analysis. For normal speech theta band (6.5-8Hz) speech-to-brain synchronization was increased and the left fronto-temporal areas generated stronger contextual predictions. The reverse was true for temporally irregular speech-weaker theta synchronization and reduced top-down effects. Interestingly, delta-band (0.5 Hz) speech tracking was greater when contextual/semantic predictions were lower or if speech was temporally jittered. We conclude that speech temporal regularity is relevant for (theta) syllabic tracking and robust semantic predictions while the joint support of temporal and contextual predictability reduces word and phrase-level cortical tracking (delta).

The evolution of the irreversible transition from a free-swimming state to an immobile sessile state in aquatic invertebrates modelled in a chemostat

To better understand the environmental factors and ecological processes underlying the evolution of the irreversible transition from a free-swimming state to an immobile sessile state as seen in many aquatic invertebrates, we study the adaptive dynamics of the settling rate of a hypothetical microorganism onto the wall of a chemostat. The two states, floating or settled, differ in their nutrient ingestion, reproduction and death rate. We consider three different settling mechanisms involving competition for space on the wall: (i) purely exploitative competition where free-swimming individuals settle in vacant space only, (ii) mixed exploitative and interference competition where individuals attempt to settle in any place but fail and die if the space is already occupied, and (iii) mixed exploitative and interference competition, but now settling in occupied space is successful and the former occupant dies. In the simplified environment of the chemostat, the input concentration of nutrients and the dilution rate of the tank are the main environmental control variables. Using the theory of adaptive dynamics, we find that the settling mechanisms and environmental control variables have qualitatively different effects on the evolution of the settling rate in terms of the direction of evolution as well as on species diversity. In the case of purely exploitative competition a small change in the settings of the environmental control variables can lead to an abrupt reversal of the direction of evolution, while in the case of mixed exploitative and interference competition the effect is gradual. For all three settling mechanisms, periodic fluctuations in the nutrient input open the possibility of evolutionary branching leading to the long-term coexistence of an intermediate and an infinitely high settling rates (in the case of low-frequency fluctuations), and an intermediate and a zero settling rates (in the case of high-frequency fluctuations).

RAS Nanoclusters: Dynamic Signaling Platforms Amenable to Therapeutic Intervention.

RAS proteins are mutated in approximately 20% of all cancers and are generally associated with poor clinical outcomes. RAS proteins are localized to the plasma membrane and function as molecular switches, turned on by partners that receive extracellular mitogenic signals. In the on-state, they activate intracellular signal transduction cascades. Membrane-bound RAS molecules segregate into multimers, known as nanoclusters. These nanoclusters, held together through weak protein–protein and protein–lipid associations, are highly dynamic and respond to cellular input signals and fluctuations in the local lipid environment. Disruption of RAS nanoclusters results in downregulation of RAS-mediated mitogenic signaling. In this review, we discuss the propensity of RAS proteins to display clustering behavior and the interfaces that are associated with these assemblies. Strategies to therapeutically disrupt nanocluster formation or the stabilization of signaling incompetent RAS complexes are discussed.

Potential and Challenges of Investigating Intrinsic Uncertainty of Hydrological Models With Stochastic, Time‐Dependent Parameters

AbstractStochastic hydrological process models have two conceptual advantages over deterministic models. First, even though water flow in a well‐defined environment is governed by deterministic differential equations, a hydrological system, at the level we can observe it, does not behave deterministically. Reasons for this behavior are unobserved spatial heterogeneity and fluctuations of input, unobserved influence factors, heterogeneity and variability in soil and aquifer properties, and an imprecisely known initial state. A stochastic model provides thus a more realistic description of the system than a deterministic model. Second, hydrological models simplify real processes. The resulting structural deficits can better be accounted for by stochastic than by deterministic models because they, even for given parameters and input, allow for a probability distribution of different system evolutions rather than a single trajectory. On the other hand, stochastic process models are more susceptible to identifiability problems and Bayesian inference is computationally much more demanding. In this paper, we review the use of stochastic, time‐dependent parameters to make deterministic models stochastic, discuss options for the numerical implementation of Bayesian inference, and investigate the potential and challenges of this approach with a case study. We demonstrate how model deficits can be identified and reduced, and how the suggested approach leads to a more realistic description of the uncertainty of internal and output variables of the model compared to a deterministic model. In addition, multiple stochastic parameters with different correlation times could explain the variability in the time scale of output error fluctuations identified in an earlier study.

Steady-State Characterization of LLC-Based Single-Stage AC/DC Converter Based on Numerical Analysis

The LLC-based single-stage ac/dc converter can achieve zero voltage switching under full load range, which offers a very attractive solution to realize high efficiency, low cost, and extreme compactness of ac/dc power conversion. However, with the introduction of LLC resonant tank in this ac/dc conversion, it becomes very challenging to accurately analyze the steady-state characterization of the converter due to its complex resonant circuit behaviors and time-varying ac input voltage. Although some analysis methods, like first-order harmonics approximation (FHA), extended FHA, and multiharmonic approximation, etc., can be adopted to analyze this converter, they cannot obtain the accurate gain curves, especially when the switching frequency deviates far from the resonant frequency. In this situation, the numerical analysis method is offered to cope with the difficulties resulting from time-varying ac input and dc output fluctuation. A set of equations describing resonant circuit behaviors, power conservation, inductor current, and capacitor voltage are presented. Also, the numerical analysis procedure is given in detail. The numerical calculation results are found that they match with those results in PSIM simulation pretty well. A 1-kW 48-V output prototype is built to verify the effectiveness of the numerical analysis.

Optimization of battery/supercapacitor-based photovoltaic household-prosumers providing self-consumption and frequency containment reserve as influenced by temporal data granularity

Service complementarity between a frequency containment reserve and PV self-consumption can increase incomes for household-prosumers. Moreover, battery/supercapacitor-based hybrid energy storage systems (HESSs) play a major role. Fitting power and energy management improve HESS performance, and therefore increase the profitability of the asset. Furthermore, component sizing is critical. To achieve both targets, we developed a hybrid meta-heuristic optimization algorithm that deals with the management strategies and sizing. Accordingly, a four-dimensional, non-linear, non-convex, and mixed-integer optimization problem was formulated, and a cost function was minimized by combining the Haar wavelet (WT) transform and the teaching-learning-based optimization (TLBO) method. The algorithm has a flexible design, which is adapted in terms of a number of discrete states to suit input profiles defined according to different time discretizations. The effectiveness of the algorithm was proved by using different data granularity for a PV prosumer in Spain in various service scenarios. The simulations performed in this study reflected both technical and economic impacts. The results suggest that for optimization purposes, high-resolution data should be used to consider the full range of input fluctuations. However, these results largely depend on the service scenario setup. Indeed, in some scenarios, accurate results were obtained by using coarse-grained data, which entailed a lower computational burden. In contrast, in other scenarios, it was preferable to use data with a higher resolution. The optimal combination of services significantly increased the profitability of the asset.

Patterns in Benthic Microbial Community Structure Across Environmental Gradients in the Beaufort Sea Shelf and Slope.

The paradigm of tight pelagic-benthic coupling in the Arctic suggests that current and future fluctuations in sea ice, primary production, and riverine input resulting from global climate change will have major impacts on benthic ecosystems. To understand how these changes will affect benthic ecosystem function, we must characterize diversity, spatial distribution, and community composition for all faunal components. Bacteria and archaea link the biotic and abiotic realms, playing important roles in organic matter (OM) decomposition, biogeochemical cycling, and contaminant degradation, yet sediment microbial communities have rarely been examined in the North American Arctic. Shifts in microbial community structure and composition occur with shifts in OM inputs and contaminant exposure, with implications for shifts in ecological function. Furthermore, the characterization of benthic microbial communities provides a foundation from which to build focused experimental research. We assessed diversity and community structure of benthic prokaryotes in the upper 1 cm of sediments in the southern Beaufort Sea (United States and Canada), and investigated environmental correlates of prokaryotic community structure over a broad spatial scale (spanning 1,229 km) at depths ranging from 17 to 1,200 m. Based on hierarchical clustering, we identified four prokaryotic assemblages from the 85 samples analyzed. Two were largely delineated by the markedly different environmental conditions in shallow shelf vs. upper continental slope sediments. A third assemblage was mainly comprised of operational taxonomic units (OTUs) shared between the shallow shelf and upper slope assemblages. The fourth assemblage corresponded to sediments receiving heavier OM loading, likely resulting in a shallower anoxic layer. These sites may also harbor microbial mats and/or methane seeps. Substructure within these assemblages generally reflected turnover along a longitudinal gradient, which may be related to the quantity and composition of OM deposited to the seafloor; bathymetry and the Mackenzie River were the two major factors influencing prokaryote distribution on this scale. In a broader geographical context, differences in prokaryotic community structure between the Beaufort Sea and Norwegian Arctic suggest that benthic microbes may reflect regional differences in the hydrography, biogeochemistry, and bathymetry of Arctic shelf systems.

Effects of Multiconstituent Tides on a Subterranean Estuary With Fixed-Head Inland Boundary

While tides of multiple constituents are common in coastal areas, their effects on submarine groundwater discharge (SGD) and salinity distributions in unconfined coastal aquifers are rarely examined, with the exception of a recent study that explored such effects on unconfined aquifers with fixed inland freshwater input. For a large proportion of the global coastline, the inland areas of coastal aquifers are topography-limited and controlled by constant heads. Based on numerical simulations, this article examines the variation of SGD and salinity distributions in coastal unconfined aquifers with fixed-head inland boundaries at different distances from the shoreline (i.e., 50, 100, 150, and 200 m). The results showed that the fluctuation intensity of freshwater input was enhanced as the inland aquifer extent decreased, e.g., the range of tide-induced fluctuations in freshwater input increased by around 5 times as the inland aquifer extent decreased from 200 to 50 m. The frequency spectra of the fluctuations of SGD and salinity distributions showed that the coastal aquifer of a shorter inland aquifer extent smoothed out fewer high-frequency tidal constituents but enhanced interaction among different tidal constituents. The interaction among tidal constituents generated new low-frequency signals in the freshwater input and salinity distributions. Regressions based on functional data analysis demonstrated that the inland freshwater input and salinity distributions at any given moment were related to the antecedent (previous) tidal conditions weighted using the probability density function of the Gamma distribution. The influence of the antecedent tidal conditions depended on the inland aquifer extent.