Water Distribution and the Impact of Relative Humidity in a PEMFC Energy System using Macroscopic Energy Representation by Inversion Control

2021 ◽  
Vol 15 (3) ◽  
pp. 57-68
Author(s):  
Farid Saadaoui ◽  
Khaled Mammar ◽  
Abdaldjabar Hazzab
Keyword(s):  
Relative Humidity ◽  
Water Distribution ◽  
Energy System ◽  
The Impact

scholarly journals Integrated sensing technologies for detection and location of leaks in water distribution networks

2017 ◽  
Vol 17 (6) ◽  
pp. 1589-1601 ◽  
Author(s):  
Alaa Hawari ◽  
Mohammad Khader ◽  
Walaa Hirzallah ◽  
Tarek Zayed ◽  
Osama Moselhi
Keyword(s):  
Relative Humidity ◽  
Water Distribution ◽  
Accurate Determination ◽  
Distribution Networks ◽  
Operating Conditions ◽  
Water Distribution Networks ◽  
Ir Camera ◽  
Efficient Operation ◽  
Leak Location ◽  
The Impact

Abstract Water distribution networks (WDNs) are infrastructure systems that have high socioeconomic values, for which efficient operation and management are required to ensure minimal amounts of waste which can be represented in the form of leaks. Leak detection is considered as one of the challenges faced by municipalities operating WDNs because it either involves shutting down the system or requires using expensive equipment and technologies. In this paper, a novel noninvasive and nondestructive methodology for detecting leaks in water pipes was tested. Ground penetrating radar was used for accurate determination of pipe location, followed by infrared (IR) thermographic imaging for determining the leak location using four different operating conditions. Results were statistically analyzed using analysis of variance and pairwise comparison methods. Several factors were found to affect the accuracy of the proposed methodology in predicting the leak location, namely, the characteristics of the studied surface (i.e. emissivity), the characteristics of the surrounding environment (i.e. ambient temperature and relative humidity), and the operating conditions of the IR camera (i.e. speed and height of the camera). The results obtained in this study have also shown that under high ambient temperatures and high relative humidity conditions, a higher speed of the IR camera would reduce the impact of noise on the collected thermal contrast and therefore, would give better leak location prediction results. The tested methodology proved the flexibility of the approach and the ability of accurately predicting the leak locations under different conditions.

scholarly journals Electric Vehicle Integration into Road Transportation, Intelligent Transportation, and Electric Power Systems: An Abu Dhabi Case Study

Smart Cities ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 1039-1057
Author(s):  
Amro M. Farid ◽  
Asha Viswanath ◽  
Reem Al-Junaibi ◽  
Deema Allan ◽  
Thomas J. T. Van der Van der Wardt
Keyword(s):  
Electric Power ◽  
Intelligent Transportation ◽  
Energy System ◽  
Transportation System ◽  
Electric Power System ◽  
Abu Dhabi ◽  
Road Transportation ◽  
Unit Distance ◽  
The Impact

Recently, electric vehicles (EV) have gained much attention as a potential enabling technology to support CO2 emissions reduction targets. Relative to their internal combustion vehicle counterparts, EVs consume less energy per unit distance, and add the benefit of not emitting any carbon dioxide in operation and instead shift their emissions to the existing local fleet of power generation. However, the true success of EVs depends on their successful integration with the supporting infrastructure systems. Building upon the recently published methodology for the same purpose, this paper presents a “systems-of-systems” case study assessing the impacts of EVs on these three systems in the context of Abu Dhabi. For the physical transportation system, a microscopic discrete-time traffic operations simulator is used to predict the kinematic state of the EV fleet over the duration of one day. For the impact on the intelligent transportation system (ITS), the integration of EVs into Abu Dhabi is studied using a multi-domain matrix (MDM) of the Abu Dhabi Department of Transportation ITS. Finally, for the impact on the electric power system, the EV traffic flow patterns from the CMS are used to calculate the timing and magnitude of charging loads. The paper concludes with the need for an intelligent transportation-energy system (ITES) which would coordinate traffic and energy management functionality.

scholarly journals Impact of temperature and relative humidity on the transmission of COVID-19: a modelling study in China and the United States

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e043863
Author(s):  
Jingyuan Wang ◽  
Ke Tang ◽  
Kai Feng ◽  
Xin Lin ◽  
Weifeng Lv ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Relative Humidity ◽  
Human Mobility ◽  
The United States ◽  
Reproductive Number ◽  
Cross Sectional ◽  
The Usa ◽  
Higher Temperature ◽  
Potential Impact ◽  
The Impact

ObjectivesWe aim to assess the impact of temperature and relative humidity on the transmission of COVID-19 across communities after accounting for community-level factors such as demographics, socioeconomic status and human mobility status.DesignA retrospective cross-sectional regression analysis via the Fama-MacBeth procedure is adopted.SettingWe use the data for COVID-19 daily symptom-onset cases for 100 Chinese cities and COVID-19 daily confirmed cases for 1005 US counties.ParticipantsA total of 69 498 cases in China and 740 843 cases in the USA are used for calculating the effective reproductive numbers.Primary outcome measuresRegression analysis of the impact of temperature and relative humidity on the effective reproductive number (R value).ResultsStatistically significant negative correlations are found between temperature/relative humidity and the effective reproductive number (R value) in both China and the USA.ConclusionsHigher temperature and higher relative humidity potentially suppress the transmission of COVID-19. Specifically, an increase in temperature by 1°C is associated with a reduction in the R value of COVID-19 by 0.026 (95% CI (−0.0395 to −0.0125)) in China and by 0.020 (95% CI (−0.0311 to −0.0096)) in the USA; an increase in relative humidity by 1% is associated with a reduction in the R value by 0.0076 (95% CI (−0.0108 to −0.0045)) in China and by 0.0080 (95% CI (−0.0150 to −0.0010)) in the USA. Therefore, the potential impact of temperature/relative humidity on the effective reproductive number alone is not strong enough to stop the pandemic.

scholarly journals Evolution of the viscoelastic properties of painting stratigraphies: a moisture weathering and nanoindentation approach

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Mathilde Tiennot ◽  
Davide Iannuzzi ◽  
Erma Hermens
Keyword(s):  
Mechanical Properties ◽  
Relative Humidity ◽  
Cultural Heritage ◽  
Mechanical Behaviour ◽  
Viscoelastic Properties ◽  
Viscoelastic Behaviour ◽  
Storage And Loss Moduli ◽  
Heritage Studies ◽  
Paint Films ◽  
The Impact

AbstractIn this investigation on the mechanical behaviour of paint films, we use a new ferrule-top nanoindentation protocol developed for cultural heritage studies to examine the impact of repeated relative humidity variations on the viscoelastic behaviour of paint films and their mechanical properties in different paint stratigraphies through the changes in their storage and loss moduli. We show that the moisture weathering impact on the micromechanics varies for each of these pigment-oil systems. Data from the nanoindentation protocol provide new insights into the evolution of the viscoelastic properties dsue to the impact of moisture weathering on paint films.

scholarly journals Modeling Bacterial Regrowth and Trihalomethane Formation in Water Distribution Systems

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 463
Author(s):  
Gopinathan R. Abhijith ◽  
Leonid Kadinski ◽  
Avi Ostfeld
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Mechanistic Model ◽  
Water Distribution Systems ◽  
Sensitivity Study ◽  
Operating Conditions ◽  
Growth Rate Constant ◽  
Model Parameters ◽  
Bacterial Regrowth ◽  
The Impact

The formation of bacterial regrowth and disinfection by-products is ubiquitous in chlorinated water distribution systems (WDSs) operated with organic loads. A generic, easy-to-use mechanistic model describing the fundamental processes governing the interrelationship between chlorine, total organic carbon (TOC), and bacteria to analyze the spatiotemporal water quality variations in WDSs was developed using EPANET-MSX. The representation of multispecies reactions was simplified to minimize the interdependent model parameters. The physicochemical/biological processes that cannot be experimentally determined were neglected. The effects of source water characteristics and water residence time on controlling bacterial regrowth and Trihalomethane (THM) formation in two well-tested systems under chlorinated and non-chlorinated conditions were analyzed by applying the model. The results established that a 100% increase in the free chlorine concentration and a 50% reduction in the TOC at the source effectuated a 5.87 log scale decrement in the bacteriological activity at the expense of a 60% increase in THM formation. The sensitivity study showed the impact of the operating conditions and the network characteristics in determining parameter sensitivities to model outputs. The maximum specific growth rate constant for bulk phase bacteria was found to be the most sensitive parameter to the predicted bacterial regrowth.

scholarly journals Decomposition Analysis of the Evolution of the Local Energy System as a Tool to Assess the Effect of Local Actions: Methodology and Example of Malmö, Sweden

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 461
Author(s):  
Isabel Azevedo ◽  
Vítor Leal
Keyword(s):  
Local Level ◽  
Ghg Emissions ◽  
Decomposition Analysis ◽  
Specific Effect ◽  
Energy System ◽  
Local Energy ◽  
Total Change ◽  
The Impact ◽  
Change Mitigation

This paper proposes the use of decomposition analysis to assess the effect of local energy-related actions towards climate change mitigation, and thus improve policy evaluation and planning at the local level. The assessment of the impact of local actions has been a challenge, even from a strictly technical perspective. This happens because the total change observed is the result of multiple factors influencing local energy-related greenhouse gas (GHG) emissions, many of them not even influenced by local authorities. A methodology was developed, based on a recently developed decomposition model, that disaggregates the total observed changes in the local energy system into multiple causes/effects (including local socio-economic evolution, technology evolution, higher-level governance frame and local actions). The proposed methodology, including the quantification of the specific effect associated with local actions, is demonstrated with the case study of the municipality of Malmö (Sweden) in the timeframe between 1990 and 2015.

scholarly journals A Hybrid Energy System Workflow for Energy Portfolio Optimization

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4392
Author(s):  
Jia Zhou ◽  
Hany Abdel-Khalik ◽  
Paul Talbot ◽  
Cristian Rabiti
Keyword(s):  
Time Series ◽  
Gaussian Process ◽  
Electricity Market ◽  
Process Model ◽  
Net Present Value ◽  
Historical Data ◽  
Energy System ◽  
Initial Guess ◽  
Reduced Order ◽  
The Impact

This manuscript develops a workflow, driven by data analytics algorithms, to support the optimization of the economic performance of an Integrated Energy System. The goal is to determine the optimum mix of capacities from a set of different energy producers (e.g., nuclear, gas, wind and solar). A stochastic-based optimizer is employed, based on Gaussian Process Modeling, which requires numerous samples for its training. Each sample represents a time series describing the demand, load, or other operational and economic profiles for various types of energy producers. These samples are synthetically generated using a reduced order modeling algorithm that reads a limited set of historical data, such as demand and load data from past years. Numerous data analysis methods are employed to construct the reduced order models, including, for example, the Auto Regressive Moving Average, Fourier series decomposition, and the peak detection algorithm. All these algorithms are designed to detrend the data and extract features that can be employed to generate synthetic time histories that preserve the statistical properties of the original limited historical data. The optimization cost function is based on an economic model that assesses the effective cost of energy based on two figures of merit: the specific cash flow stream for each energy producer and the total Net Present Value. An initial guess for the optimal capacities is obtained using the screening curve method. The results of the Gaussian Process model-based optimization are assessed using an exhaustive Monte Carlo search, with the results indicating reasonable optimization results. The workflow has been implemented inside the Idaho National Laboratory’s Risk Analysis and Virtual Environment (RAVEN) framework. The main contribution of this study addresses several challenges in the current optimization methods of the energy portfolios in IES: First, the feasibility of generating the synthetic time series of the periodic peak data; Second, the computational burden of the conventional stochastic optimization of the energy portfolio, associated with the need for repeated executions of system models; Third, the inadequacies of previous studies in terms of the comparisons of the impact of the economic parameters. The proposed workflow can provide a scientifically defendable strategy to support decision-making in the electricity market and to help energy distributors develop a better understanding of the performance of integrated energy systems.

scholarly journals A novel mouse model of heatstroke accounting for ambient temperature and relative humidity

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Kazuyuki Miyamoto ◽  
Keisuke Suzuki ◽  
Hirokazu Ohtaki ◽  
Motoyasu Nakamura ◽  
Hiroki Yamaga ◽  
...  
Keyword(s):  
Gene Expression ◽  
Body Temperature ◽  
Relative Humidity ◽  
Ambient Temperature ◽  
Core Body Temperature ◽  
Heat Exposure ◽  
Organ Damage ◽  
Core Body ◽  
The Impact ◽  
Treatment Water

Abstract Background Heatstroke is associated with exposure to high ambient temperature (AT) and relative humidity (RH), and an increased risk of organ damage or death. Previously proposed animal models of heatstroke disregard the impact of RH. Therefore, we aimed to establish and validate an animal model of heatstroke considering RH. To validate our model, we also examined the effect of hydration and investigated gene expression of cotransporter proteins in the intestinal membranes after heat exposure. Methods Mildly dehydrated adult male C57/BL6J mice were subjected to three AT conditions (37 °C, 41 °C, or 43 °C) at RH > 99% and monitored with WetBulb globe temperature (WBGT) for 1 h. The survival rate, body weight, core body temperature, blood parameters, and histologically confirmed tissue damage were evaluated to establish a mouse heatstroke model. Then, the mice received no treatment, water, or oral rehydration solution (ORS) before and after heat exposure; subsequent organ damage was compared using our model. Thereafter, we investigated cotransporter protein gene expressions in the intestinal membranes of mice that received no treatment, water, or ORS. Results The survival rates of mice exposed to ATs of 37 °C, 41 °C, and 43 °C were 100%, 83.3%, and 0%, respectively. From this result, we excluded AT43. Mice in the AT 41 °C group appeared to be more dehydrated than those in the AT 37 °C group. WBGT in the AT 41 °C group was > 44 °C; core body temperature in this group reached 41.3 ± 0.08 °C during heat exposure and decreased to 34.0 ± 0.18 °C, returning to baseline after 8 h which showed a biphasic thermal dysregulation response. The AT 41 °C group presented with greater hepatic, renal, and musculoskeletal damage than did the other groups. The impact of ORS on recovery was greater than that of water or no treatment. The administration of ORS with heat exposure increased cotransporter gene expression in the intestines and reduced heatstroke-related damage. Conclusions We developed a novel mouse heatstroke model that considered AT and RH. We found that ORS administration improved inadequate circulation and reduced tissue injury by increasing cotransporter gene expression in the intestines.

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