Moisture Flow Research Articles

Numerical Modelling for effect of rainfall on unsaturated soil slopes

Expansive soils are predominant in many parts of the world. Expansive soil treated as problematic soils, as economic and design a safe slope on expansive soils is major challenge for civil engineers. Expansive soils were compacted under unsaturated condition, in various construction projects. Major failures reported in many countries around the world are due to swell shrinkage characteristics causing unstable slopes. Fills and compacted soils have an inherent suction when they are first compacted. The suction is the most important factor which affects the shear strength of unsaturated soil. variation of suction in unsaturated soil is an important factor considered for solving issues like slope stability and bearing capacity failure in unsaturated soil. Rainwater infiltration are major triggering factor for failureof expansive soil slopes. The strength of unsaturated soil changes with water evaporation and infiltration. Due to infiltration of rainwater into the soil a significant change in the pore water takes place. Hence, this fluctuation in pore water pressure responsible for the distinct mechanical behavior of unsaturated soil under different Geotechnical problems.A numerical modeling was done with Plaxis LE software, considering parameters of unsaturated soil. As the changes in pore-water pressure and moisture content are a function of the flow of moisture through the soil-atmosphere boundary.The effect of soil type, rainfall intensity, location of ground water table, permeability functionsareconsidered to reproduce the soil-atmosphere interaction. Obtain results illustrates the combine effect of suction and increase of saturation due to rainfall on slopes. It was observed that rainfall increase the induced matric suction and increase the positive pore water pressure finally results in slope failures.

Landslide Monitoring and Detection

The project titled "Landslide Monitoring and Detection" aims to detect and monitor potential landslides using a combination of sensors and machine learning algorithms. The sensors used in this project are MQ, rainfall, vibration, soil moisture, DHT, and water flow sensors. These sensors collect data that is sent to an Arduino Uno, which then sends it to a Node MCU. The Node MCU sends the data to a Java server using NetBeans IDE, which stores the data in a text file. The machine learning algorithms used in this project are KNN, random forest, XGBoost, and decision tree. These algorithms are applied to the data in the text file, with a given threshold value based on training data, to determine which algorithm provides the best accuracy. The algorithm with the highest accuracy is then used as the result for landslide detection and monitoring. The use of multiple sensors and machine learning algorithms improves the accuracy of landslide detection and monitoring. The sensors provide real-time data that is continuously monitored and analyzed by machine learning algorithms. The results of this project can aid in preventing and mitigating the effects of landslides, which can cause significant damage to infrastructure and loss of life. This project has the potential to be implemented in areas prone to landslides, providing early warning systems and improving disaster management strategies.

Mathematical Simulation of Honeycomb Weathering via Moisture Transport and Salt Deposition

Honeycomb weathering is a common phenomenon found on various rock surfaces all around the world. However, honeycomb formation mechanisms are still poorly understood. In this study, we propose a model describing moisture transport within the sandstone and erosion resulting from salt deposition during evaporation of moisture off the rock surface. The moisture transport model is based on the non-linear diffusion equation, where the volumetric moisture content is a combined parameter accounting for the moisture and gas (vapor) content. The moisture transport model accounts for the several-orders-of-magnitude decrease in moisture diffusivity, observed during drying. It was assumed that erosion occurs when the evaporation front is located close to the rock surface. The depth of erosion is proportional to the moisture flow rate through the drying surface. The ABAQUS finite-element software suite was used for numerical solution of the non-linear diffusion equation. The iterative scheme of erosion simulation for different drying cycles was implemented using the Python programming language. Computations were conducted in the 2D setting for the square model with dimensions of 50 mm × 50 mm. Simulation results demonstrate the possibility of obtaining various landform shapes (honeycombs, tafoni) by varying only the value of the distribution of moisture content at the bottom side, simulating the rate of internal wetting of rock.

Risk analysis of meteorological, agricultural, and hydrological drought events and study of drought propagation features: a case study in the upper Tapti River sub-basin, Central India

Abstract As a natural hazard, drought is a complex multivariate phenomenon that requires more comprehensive analysis. In this study, we studied meteorological, agricultural, and hydrological drought events with precipitation, soil moisture, and stream flow data for the study area. The risk analysis for drought duration and severity of three kinds of drought events were analyzed with univariate and three kinds of bivariate return periods based on the copula. Furthermore, the propagation of three kinds of drought was studied. From the investigation, it is observed that agricultural drought events are longer and more severe, besides the risk associated with agricultural drought is high compared to other kinds of drought. Moreover, the average time taken for meteorological drought to propagate into agricultural drought is 4.3 months and for the hydrological drought is 3.8 months for the river basin. The comprehensive study of three kinds of drought is helpful to adopt suitable drought management plans in the region.

A probabilistic framework for assessing the hydrological impact of Faidherbia albida in an arid area of Senegal

The Faidherbia tree (Faidherbia albida) is frequently used as an intercrop in Sahelian agroforestry parklands due to its multi-purpose advantages and reverse phenology. However, its effect upon the water balance remains unclear, due to the challenges in directly measuring water fluxes in the underlying vadose zone. Mechanistic hydrological models can be inversely calibrated on transient observations and used to partition different hydrological components, but the computational burden of the analysis can become impractical if the model itself is computationally expensive. To overcome this limitation, and to provide novel insights into the hydrological role of Faidherbia, we combine a low-fidelity, one-dimensional hydrological model (HYDRUS-1D) with a kriging-based correction function to emulate the response of a high-fidelity, two-dimensional axisymmetric description of the system (HYDRUS-2D). Multiannual measurements of soil moisture and sap flow in a Senegal agroforestry parkland are used in conjunction with Bayesian inference to calibrate the resulting validated multifidelity surrogate, and to inversely estimate soil hydraulic and root water uptake parameters. Results show that the model can reproduce observations with good accuracy and limited uncertainty for both the calibration and the validation phases, and also confirm the phreatophytic behaviour of Faidherbia by indicating the existence of a moderately compensated root water uptake. Moreover, a local sensitivity analysis suggests that a fully compensated uptake could potentially reduce groundwater recharge by 13%. Interestingly, estimated soil hydraulic parameters hint at the possibility of root-induced changes in soil hydraulic properties that mimic preferential and/or macropore flow, resulting in sustained recharge fluxes (≈ 26% of the annual precipitation). The analysis indicates that overall, Faidherbia could have a net positive effect upon the water balance in arid areas.

Two Case Studies of the Northwestern Argentinean Low: With and without a Coupled Transient Trough

The Northwestern Argentinean Low (NAL) intensifies the zonal component of the geopotential gradient to its east, intensifying the meridional wind and moisture flow from the tropics to the subtropics contibuting importantly to the South American Low-Level Jet and the Chaco Jet. This study compares two situations where the NAL is present in the continent’s subtropics: one where it is coupled with an extratropical transient trough to its south and another without this coupling. The coupled case, called the front case, is stronger in two ways: it is warmer and shows lower geopotential at the center of the NAL. It also shows much stronger moisture transport. Both cases show a similar trait in that moisture transport and the zonal component of the geopotential gradient east of the NAL peak in the coolest hours. The geopotential at the center of the no-front case remains roughly constant throughout the event. For the front case, it attains its minimum value in the six hours preceding the northeastward advance of the transient trough. These results suggest that there are different mechanisms acting at the center of the NAL and at its eastern branch, as well as in the front and no-front cases.

A Strategical Improvement in the Performance of CO2/N2 Gas Permeation via Conjugation of L-Tyrosine onto Chitosan Membrane

Rubbery polymeric membranes, containing amine carriers, have received much attention in CO2 separation because of their easy fabrication, low cost, and excellent separation performance. The present study focuses on the versatile aspects of covalent conjugation of L-tyrosine (Tyr) onto the high molecular weight chitosan (CS) accomplished by using carbodiimide as a coupling agent for CO2/N2 separation. The fabricated membrane was subjected to FTIR, XRD, TGA, AFM, FESEM, and moisture retention tests to examine the thermal and physicochemical properties. The defect-free dense layer of tyrosine-conjugated-chitosan, with active layer thickness within the range of ~600 nm, was cast and employed for mixed gas (CO2/N2) separation study in the temperature range of 25-115 °C in both dry and swollen conditions and compared to that of a neat CS membrane. An enhancement in the thermal stability and amorphousness was displayed by TGA and XRD spectra, respectively, for the prepared membranes. The fabricated membrane showed reasonably good CO2 permeance of around 103 GPU and CO2/N2 selectivity of 32 by maintaining a sweep/feed moisture flow rate of 0.05/0.03 mL/min, respectively, an operating temperature of 85 °C, and a feed pressure of 32 psi. The composite membrane demonstrated high permeance because of the chemical grafting compared to the bare chitosan. Additionally, the excellent moisture retention capacity of the fabricated membrane accelerates high CO2 uptake by amine carriers, owing to the reversible zwitterion reaction. All the features make this membrane a potential membrane material for CO2 capture.

Application of GIS‐based DRASTIC model and its validation with Solute Transport Model in the assessment of groundwater vulnerability index: A case study from coal mining region of India

AbstractThe intensive Coal mining in Dhanbad, India, is crucial for contaminating the groundwater resources. The present work aims to estimate the vulnerability of aquifers to contamination with the aid of a GIS‐based DRASTIC approach. This is finally validated by comparing the concentration of the contaminant computed by the Solute Transport Model. Using the soil moisture flow and pollutant transport model, an effort is made to validate the vulnerability of groundwater pollution. The vulnerability maps showed that some of this region's western southwest, and northern part lies in the highly vulnerable region. The major influential parameters in the present study for mapping the vulnerability are shallow depth to groundwater, higher net recharge and more permeable vadose zone. Furthermore, the surrounding mining activities are highly accountable for depleting groundwater superiority in the present research area. These vulnerability maps can be later on effectively used for environmental development and managing future water resources. The Solute Transport Model does not compute vulnerability; instead, it computes the concentration of the contaminant.

Investigating the use of electrical capacitance tomography to image rapid transient moisture flow through cracks in concrete

In this paper, we investigate the feasibility of electrical capacitance tomography (ECT) to image rapid three-dimensional (3D) moisture transport in damaged portland cement mortar and concrete. ECT is a tomography method that uses inter-electrode capacitance measurements to reconstruct the internal 3D distribution of the electrical permittivity which carries contrast with respect to moisture content. In the experimental study, ECT measurements were performed with a reservoir placed directly on the crack in each specimen to promote rapid moisture transport to test the high temporal resolution capabilities. An electrode array connected to an electrical tomography device was used to conduct moisture transport measurements in cracked specimens at a temporal resolution as high as 0.7 s. The results of this study illustrate that ECT can be used to detect rapid moisture transport through various crack patterns and capture the flow path of water around coarse aggregates with potential use for field monitoring.

Optimization Formula of Coffee-Maca Granules as an Aphrodisiac Functional drink using D-Optimal mixture Design and PCA-CA

Arabica coffee (Coffea arabica) and maca (Lepidium mayenii) have many health benefits, one of which is as a tonic and aphrodisiac. This study aimed to combine coffee and maca into a functional drink that has health benefits. Formula optimization was carried out by the D-Optimal Mixture Design method using the proportion of coffee, maca, and dextrin as research variables. The research observed were the amount of yield, moisture content, flow rate, compressibility index, and mounting frequency of male rats to see the aphrodisiac effect. Principal Component Analysis-Cluster Analysis (PCA-CA) was used to study the relationship between experimental responses and the correlation between formulas. The results showed that three components such as coffee, maca, and dextrin gave a positive response in increasing yield values and compressibility index. Meanwhile, foor experimental responses such as moisture content, flow rate, and aphrodisiac tests only two components namely, coffee and maca, gave a positive response in increasing the response. The optimum formula for coffee-maca granules resulted in the average yield value, moisture content, flow rate, compressibility index and mounting frequency of 29.08 g, 5.09%, 5.98, 0.18%, and 10.67, respectively.

Remotely Sensed Soil Moisture Assimilation in the Distributed Hydrological Model Based on the Error Subspace Transform Kalman Filter

The data assimilation of remotely sensed soil moisture observations provides a feasible path of improving river flow simulation. In this work, we studied the performance of the error subspace transform Kalman filter (ESTKF) assimilation algorithm on the assimilation of remotely sensed soil moisture from SMAP, including the improvement of soil moisture and river flow in the hydrological model. Additionally, we discussed the advantages and added value of ESTKF compared to the ensemble Kalman filter (EnKF) in a hydrological model. To achieve this objective, we solved the spatial resolution gap between the remotely sensed soil moisture and the simulated soil moisture of the hydrological model. The remotely sensed soil moisture from SMAP was assimilated into the first layer soil moisture in the distributed hydrological model. The spatial resolution of the hydrological model was 600 m, while the spatial resolution of the SMAP remotely sensed soil moisture was 9 km. There is a considerable gap between the two spatial resolutions. By employing observation operators and observation localization based on geolocation, the distributed hydrological model assimilated multiple remotely sensed soil moisture values for each grid, thereby ensuring the consistent updates of soil moisture in the model. The results show the following: (1) In terms of improving soil moisture, we found that both ESTKF and EnKF were effective, and the ubRMSE of ESTKF was lower than that of EnKF. (2) ESTKF improved most cases where open-loop high river flow simulations were too low, but EnKF did not improve this situation. (3) In ESTKF, the relative error of flood volume was reduced on average to 2.52%, but the relative error of flood peak did not improve. The results provide evidence of the value of ESTKF in the hydrological model.

Characteristics of cloud properties over South America and over Andes observed using CloudSat and reanalysis data

ABSTRACT CloudSat profile of attenuated corrected radar reflectivity (Ze) and cloud mask data are used to investigate the cloud properties over South America (SA) during Austral Summer monsoon seasons. Deep convective core (DCC), deep & intense convective systems (DCSs & ICSs), and cloud clusters (CCs) are defined based on the Ze and cloud mask values. The spatial distributions of DCCs show that land-dominated areas have higher frequency of DCCs and Atlantic Ocean has less DCCs. The Pacific Ocean does not consist of DCCs, whereas eastern flank of Andes has higher frequency of DCCs compared to western flank of the Andes. North La Plata basin (Sierra de Cordoba) has a higher fraction of deeper (shallower) DCCs. Deep convection over the Sierra de Cordoba and South La Plata Basin is characterized by precipitation-size particles compared to cloud-size particles, whereas deep convection over north La Plata Basin is dominated by mostly cloud-size particles. The horizontal span of DCSs and ICSs is higher over south La Plata Basin and Atlantic Oceans compared to other SA areas. Sierra de Cordoba (Atlantic Ocean) has the highest (lowest) frequency of small DCSs and vice versa. DCSs and ICSs show the opposite characteristic, as all the selected areas consist of a higher fraction of large (small) sized DCSs (ICSs). CCs develop more in horizontal than in vertical direction over the high latitude and vice versa over lower latitude. The CCs distribution reflects the orography and moisture flow pattern at the east and west side of Andes. The higher Ze, which is the proxy for rainfall, occurs at the eastern flank/slope of the Andes, and related to easterly moisture loaded synoptic flow, transported from Amazon and upslope flow along the slope.

Super-resolution and uncertainty estimation from sparse sensors of dynamical physical systems

The goal of this study is to leverage emerging machine learning (ML) techniques to develop a framework for the global reconstruction of system variables from potentially scarce and noisy observations and to explore the epistemic uncertainty of these models. This work demonstrates the utility of exploiting the stochasticity of dropout and batch normalization schemes to infer uncertainty estimates of super-resolved field reconstruction from sparse sensor measurements. A Voronoi tessellation strategy is used to obtain a structured-grid representation from sensor observations, thus enabling the use of fully convolutional neural networks (FCNN) for global field estimation. An ensemble-based approach is developed using Monte-Carlo batch normalization (MCBN) and Monte-Carlo dropout (MCD) methods in order to perform approximate Bayesian inference over the neural network parameters, which facilitates the estimation of the epistemic uncertainty of predicted field values. We demonstrate these capabilities through numerical experiments that include sea-surface temperature, soil moisture, and incompressible near-surface flows over a wide range of parameterized flow configurations.

Quantifying the Fingerprint of Oceanic Moisture Source Conditions in Deuterium and 17O Excess Parameters of Precipitation

AbstractThe deuterium excess (d‐excess) and more recently developed 17O excess (Δ′17O) of precipitation are isotopic tracers that are sensitive to oceanic moisture source (OMS) conditions. However, other regional and local processes also affect precipitation d‐excess and Δ′17O and may modify or overprint their OMS signals. Here, I leverage the new atmospheric moisture flow data set to diagnose the OMS regions and conditions globally and show that OMS temperature and relative humidity together explain 41% of the variability in monthly mean precipitation d‐excess in low‐ and mid‐latitudes. Based on a few sites currently having paired d‐excess and Δ′17O data, I also show that the contrasting sensitivity between d‐excess and Δ′17O to OMS temperature, which is initially predicted by theory, is distinguishable from precipitation observations under annual mean conditions. This study contributes to disentangling the complex controls on precipitation d‐excess and Δ′17O by quantifying the crucial role of OMS dynamics.

Effects of deforestation and forest degradation on ecosystem service indicators across the Southwestern Amazon

The Southwestern Amazon (SWA) is home to one of the Earth́s remaining intact ecosystems and a key provider of continental atmospheric moisture flows. However, the integrity of this region is threatened by global changes in climate and local to regional changes in land-use and land-cover. Here, unlike most Amazonia-land-change research which has focused primarily on deforestation, we evaluated the effects of both deforestation and forest degradation on three Ecosystem Service Indicators (ESIs) – evapotranspiration (ET), land surface temperature (LST), and precipitation (P) – at the local and watershed scale across the SWA between 2003 and 2020. We computed annual and monthly ESI differences over distinct forest conditions and buffers around disturbed areas (degraded or deforested). We also determined the influence of forest disturbance trends on ESI trends at the pixel and watershed level through a Partial Mann-Kendall approach. The results show that ESI differences among different forest conditions are statistically-significant and more pronounced during the dry season. In comparison with intact forest, monthly P rates were up to 25 % lower over any type of disturbance; whereas ET rates were up to 15 % and 48 % lower, and LST rates up to 1.6 °C and 4.4 °C higher, over degraded and deforested areas, respectively. ET and LST edge effects were only significant within buffers around some of the most heavily disturbed areas. At the pixel scale, negative trends in ET and positive trends in both LST and P were more frequently explained by forest disturbances as these trends themselves become more pronounced. ET and LST trends determined by disturbances were generally located near roads, rivers, and human settlements; and surprisingly, we found that degradation more often influences these trends than deforestation, which we attribute to the practice of converting deforested areas into crops whose growing season ET and LST rates are similar to those in natural vegetation. At the watershed scale, the analysis suggested that the climate implications of degradation and deforestation have not scaled up to this level yet; however, literature has shown that even the local impacts we report here can have important implications for areas outside of the SWA, which emphasizes the importance of continuing to conserve this remote region.

Optimization of asphalt mixture design using response surface method for stone matrix warm mix asphalt incorporating crumb rubber modified binder

The use of crumb rubber as an asphalt bitumen performance improver has received special attention. The high viscosity of crumb rubber modified binder (CRMB) and the need for high production temperatures in mixtures containing this type of bitumen necessitate the use of warm mix asphalt (WMA) technology. One of the important applications of CRMB is in special-use mixtures such as stone matrix asphalt (SMA). This study aimed to determine the optimal design of stone matrix warm mix asphalt containing CRMB. Therefore, the response surface method (RSM) was used to develop the response prediction models. Production temperature and the content of polyethylene wax and CRMB were considered independent variables of the study. Moisture sensitivity, flow number, resilient modulus, and critical stress intensity factor were used as response (dependent) variables to determine the optimal design of the mixture. The results showed that the prediction models of response variables can predict the performance results with acceptable accuracy. Production temperature and polyethylene wax content are the most important factors in prediction models. To achieve the optimal design of the mixture, minimizing the production temperature and resilient modulus and maximizing the flow number, resistance to moisture susceptibility, and critical stress intensity factor led to the achievement of desirable solutions. The optimal design of stone matrix warm mix asphalt containing CRMB at 135 °C, 7.02 % CRMB, and 2.1 % polyethylene wax using predictive models with 0.765 desirability were obtained.

Climatology Definition of the Myanmar Southwest Monsoon (MSwM): Change Point Index (CPI)

Myanmar’s climate is heavily influenced by its geographic location and relief. Located between the Indian summer monsoon (ISM) and the East Asian summer monsoon (EASM), Myanmar’s climate is distinguished by the alternation of seasons known as the monsoon. The north-south direction of peaks and valleys creates a pattern of alternate zones of heavy and scanty precipitation during both the northeast and southwest monsoons. The majority of the rainfall has come from Myanmar’s southwest monsoon (MSwM), which is Myanmar’s rainy season (summer in global terms, June–September). This study explained both threshold-based and nonthreshold-based objective definitions of the onset and withdrawal of large-scale MSwM. The seasonal transitions in MSwM circulation and precipitation are convincingly represented by the new index, which is based on change point detection of the atmospheric moisture flow converging in the MSwM region (10–28 N, 92–102 E). A transition in vertically integrated moisture transport (VIMT), the reversal of surface winds, and an increase in precipitation may also be considered when defining MSwM onset objectively. We also define a change point of the MSwM (CPI) index for MSwM onset and withdrawal dates. The climatological mean onset of MSwM is day 135 (May 14), withdrawal is day 278 (October 4), and the total season length is 144 days. We are investigating spatial patterns of rainfall progression at and after the start of the monsoon, rather than transitions within a single region of the MSwM. The local southwest monsoon duration is well correlated with the CPI duration on interannual timescales, particularly in the peak rainfall regions, with a delay (advance) in large-scale onset or withdrawal associated with a delay (advance) of onset or withdrawal by local index. Hence, the next phase of this research is to study the maintenance and break of the monsoon to understand the underlying physical processes governing the monsoon circulation. The results of this study provide a possibility to reconstruct Myanmar’s monsoon climate dynamics, and the findings of this study can help unravel many remaining questions regarding the greater Asian monsoon system’s variability.

Influence of the shives orientation on selected hygro-thermal properties of hemp-magnesium composite

Magnesium binder is an alternative to lime binder in the technology of hemp-based composites. The advantage of using this binder is an increase in mechanical strength compared to those based on lime. These composites are mainly used as an insulating wall material, as a filling of a wooden frame structure. During compaction of the mixture, hemp shives tend to lay with fibers perpendicular to the compaction direction. The direction of the fibers in the shives, as well as the direction of the capillary pores affect the properties of the composite. The performance characteristics of a building partition insulated with a composite will vary depending on the direction of the shives in relation to the direction of the external factor. The outer wall is exposed to heat flow and water transport, e.g. by capillary action. The article presents the results of tests of the thermal conductivity and capillary rise of a composite densified in the direction perpendicular and parallel to the heat flux and moisture flow. Composites samples with a bulk density of about 370 kg/m3 were tested. Compaction of the mixture in the direction parallel to the heat flow decreased the thermal conductivity. Due to the reduced value of the thermal conductivity of the composite compacted parallel to the heat flux, such a technique can be used in prefabrication, e.g. in the production of wall blocks. This direction of compaction - perpendicular to the wall surface, and thus to the direction of capillary rise, also reduced the amount of uptaken up water and changed the course of water rising over time.

Climate-driven soil suction variation using a natural-order Fourier series approach

In unsaturated soil practice, the near-ground-surface moisture flow is commonly evaluated using the 1-dimensional (1D) suction diffusion equation. This study presents the application of a Natural-Order Fourier Series (NOFS) approach for representing monthly climate-driven soil suction variations near the ground surface, which is a boundary condition that is generally difficult to adequately model. The NOFS incorporates an algorithmic selection criterion to optimize the order of the Fourier series to improve the capture of the seasonal shifts and extreme climate periods, while maintaining acceptable computation efficiency. The climate-soil suction interaction is expressed using published empirical relationships between monthly rainfall, temperature, and soil index properties. An example and validation study of the proposed NOFS selection approach is presented using measured soil properties and historical weather data at a study site in Denver, Colorado USA. Key findings from performance and stability studies of five locations in the United States associated with differing climate regions are discussed. Limitations and recommendations for implementation are also included. The proposed NOFS approach for capturing climate-driven changes in suction near the ground surface can be efficiently implemented in unsaturated soil numerical analyses that are governed by moisture-dependent mechanical soil behavior and can help improve the computation time, stability, and performance associated with stochastic simulations.

Ergonomic Evaluation of Anthropometry Based Hydroponic Plants Watering Automation System

Hydroponics is a technique of growing plants without soil. Until now, many people do it manually for moisture, content, nutrition, and continuous flow of water. The application of ergonomics aims to make the user healthy, comfortable, safe, productive. The purpose of evaluating anthropometry-based ergonomics, and testing the hydroponic plant watering automation system tool. The method used is collecting anthropometric data on the dimensions of the user's body for ergonomics, then designing an automatic hydroponic watering tool to make it easier to design hardware and software. The results of the ergonomics evaluation study, hand span size 175.3 cm, upright body height 167.4 cm, shoulder to head 32.23 cm, shoulder to base of foot 66.77 cm, base of foot to knee 48.89 cm, base of foot to knee 48.98 cm, elbow to elbow 41.81 cm, elbow to hand 34.45 cm. While the results of testing the condition of the charcoal are at the humidity threshold of 49% - 60% then the pump will be on, and if the pot has been on the humidity threshold of 65% - 99% then the pump will be off.