Constant Depth Research Articles

Numerical simulation and optimization of sweep angle and depth variation studies for enhanced performance of savonius turbine

The straightforward and dependable Savonius turbine has a lot of promise for capturing wind energy in low-speed settings. However, poor aerodynamic performance frequently restricts its effectiveness. This study uses numerical modeling methods to examine how different sweep angles with constant depth affect Savonius turbine performance. The turbine's aerodynamic behaviour, torque production, and power coefficient were examined using parametric sweep optimization in various sweep angle with constant depth and fixed sweep angle with variable depth configurations. The results highlight the influence of sweep angle and depth on flow characteristics, lift to drag ratio, Torque and Power coefficient, leading to an optimized design with enhanced energy conversion efficiency. The findings provide valuable insights into improving the aerodynamic performance of Savonius turbines, contributing to their viability in sustainable energy applications.

A Computational Study of Dielectric Properties of Coconut Shell Powder and Coconut Shell-Activated Carbon and Organic Soil

This study investigates the dielectric properties of artificial soil mixtures created using Coconut Shell Powder (CSP), Coconut Shell-Activated Carbon (CSAC), and Organic Soil. CSP, known for its lightweight and excellent water retention capacity, was combined with CSAC, renowned for its superior adsorption properties and enhanced conductivity. Organic Soil, rich in nutrients, served as a base material for improving soil texture and supporting plant growth. Three mixtures were prepared in ratios of 50% CSP, 30% CSAC, and 20% Organic Soil; 60% CSP, 20% CSAC, and 20% Organic Soil; and 40% CSP, 40% CSAC, and 20% Organic Soil. The dielectric constant, dielectric loss factor, loss tangent, conductivity, and skin depth were analyzed using Lichtenecker's logarithmic mixture model and MATLAB simulations. Results revealed that the mixture with 50% CSP, 30% CSAC, and 20% Organic Soil exhibited the highest dielectric constant and skin depth, indicating its potential for soil moisture sensing, energy storage, and electromagnetic shielding applications. This innovative approach highlights the benefits of CSP and CSAC in artificial soil development for sustainable agriculture and urban greening.

Three-dimensional time-dependent water flows with constant non-vanishing vorticity and depth dependent density

Three-dimensional time-dependent water flows with constant non-vanishing vorticity and depth dependent density

Modeling of soil salinity in Rheris Oasis (Southeastern of Morocco) using satellite spectral indices

The Rheris oases in Southeastern Morocco are an essential ecosystem. It presents enormous ecological and natural values. Water scarcity coupled with agricultural intensification results in soil salinization and its degradation. This work aims to propose a spatiotemporal monitoring method of soil salinization in the Rheris oasis using spectral indices derived from Thematic Mapper (TM) and Operational Land Imager (OLI) data. The most used indices in the literature were (14 indices) tested and correlated with the results obtained from 50 samples taken from the first soil horizon at a constant depth of 0.20 m from the November 2022 campaign. The findings confirm that this method is highly effective and reliable for the modeling and spatial mapping of soil salinity in this region. The state of the hydroclimate is an aspect that influences soil salinization. An increase in salinized surfaces is observed during the periods of 1990–1996, 2000–2005, and 2017-2022. The spatio-temporal distribution of saline soils in Rheris Oasis is very variable. The monthly variations are more important than the annual ones.

Identification of parameter-dependent machine learning models for tool flank wear prediction in dry titanium machining

This study uses machine learning (ML) techniques to predict maximum flank wear on cutting tools during the turning of Ti6Al4V, a titanium alloy known for its challenging machinability. We used three models (a) support vector machines (SVM), (b) random forests (RF), and (c) neural networks (NN) to predict maximum flank wear. The machining parameters are taken as input data sets, which compromise cutting speed, feed, and machining time. All the experiments are done at a constant depth of cut to predict maximum flank wear as an output variable. The forecasted maximum flank wear was validated using experimental data to verify their precision. The SVM model outperformed the other ML models in a wider range of cutting parameters concerning tool flank wear. The SVR model is the most accurate model with an average forecasting error of 3.24%. In forecasting maximum flank wear, the RF and NN models followed, with average forecasting errors of 3.88% and 3.71%, respectively. Additionally, the SVM model's robustness was further validated by its ability to maintain stability at varying cutting speeds and feed rates. The research enhances the economics of the machining process by predicting tool flank wear and fostering sustainability in the manufacturing industry, thereby demonstrating the applicability of ML techniques.

State preparation by shallow circuits using feed forward

Fault tolerant quantum computers repetitively apply a four-step procedure: First, perform a few one and two-qubit quantum gates. Second, perform a syndrome measurement on a subset of the qubits. Third, perform fast classical computations to establish if and where errors occurred. And, fourth, correct the errors with a correction step. The next iteration applies the same procedure with new one and two-qubit gates. Even though current error-rates prohibit this procedure to work and fault tolerant quantum computing remains a distant goal, the same procedure can already prove useful today. In this work we make use of this four-step scheme not to carry out fault-tolerant computations, but to enhance short, constant-depth, quantum circuits that perform 1 qubit gates and nearest−neighbor 2 qubit gates.We introduce a new computational model called Local Alternating Quantum Classical Computations(LAQCC). In this model, qubits are placed in a grid and they can only interact with their direct neighbors; the quantum circuits are of constant depth with intermediate measurements; a classical controller can perform log-depth computations on these intermediate measurement outcomes and control future quantum operations based on the outcome. This model fits naturally between quantum algorithms in the NISQ era and full-fledged fault-tolerant quantum computation. We first prove that any Clifford circuit has an equivalent LAQCC circuit, and that any LAQCC circuit can be simulated by a QNC1circuit. Next, we conjecture the non-simulatability of LAQCC by showing that LAQCC contains the class of Instantaneous Quantum Polynomial-time circuits. We also show that any LAQCC circuit with polynomial-sized quantum circuits and unbounded classical computations is contained in the class of quantum circuits equipped with post-selection gates with respect to the task of state preparation. We continue by presenting LAQCC implementations of different subroutines, including OR-gates, quantum Fourier transforms and Threshold gates. These subroutines prove vital in constructing three state preparation routines in the main part of this work. Preparing a uniform superposition uses constant-depth arithmetic gates, combined with an exact Grover implementation by Long. For the W-state, we employ a compress-uncompress method to switch between a binary and one-hot encoding. This method extends to the more generalized Dicke-states, the superposition of n-bit strings of Hamming weight k, for k=O(n), but fails for higher k due to the birthday paradox. We extend this protocol to a protocol that prepares many-body scar states, highly excited states with low entanglement and longer coherence times than states with the same energy density. We present a circuit for preparing Dicke-states for larger k requiring log-depth circuits that maps between the factoradic number system and the combinatorial number system.

Influence of cryogenically treated hob on surface characteristics of spur gear

ABSTRACT This work presents a comparative study of the surface characteristics of spur gears produced from cryotreated and untreated hobs at various cutting speeds and feed rates keeping constant depth of cut. Furthermore, a Taguchi Grey Relational Analysis was used to optimize the hobbing process and ANOVA was conducted to analyze the influence of studied parameters. The experimental run, for which the highest gray relational grade was obtained, was considered the optimal cutting condition. The results revealed that cryogenic treatment of the hob significantly decreased the spur gear’s flank surface roughness ( R a and R max ) and microgeometric deviations ( F a , F β , F p and F r ). The optimization results revealed that a cutting speed of 400 rpm and a feed of 8 mm/min with a cryo-treated hob produced the best surface characteristics (i.e. R a = 0.30 μ m , R max = 2.77 μ m , F a = 10.60 μ m , F β = 20.03 μ m , F p = 10.40 μ mand F r = 20.20 μ m ). This study can assist manufacturing industries in selecting suitable operating parameters for obtaining high-quality gears.

Time-series models and biotelemetry identify behavioral dynamics within a spawning aggregation of a large marine predator

Fish spawning aggregations (FSAs) may persist for months and include behaviors such as spawning and foraging. Acoustic telemetry has been used to measure the movements of fishes to and from FSAs, but behaviors within the aggregation are harder to quantify. We used multi-sensor acoustic telemetry (depth, acceleration) combined with continuous wavelet transformation analysis and hidden Markov models to identify behaviors within a spawning aggregation of the goliath grouper Epinephelus itajara, a vulnerable marine predator. Tagged fish (n = 20) exhibited periods (over 2 spawning seasons, August-October) where multiple individuals displayed variability in depth just after the new moon. These events may represent spawning, and there was always one event each season that included a greater number of individuals and more variability in depth. Grouper were more active during the new moon, in shallow water (<15 m), and at night. We also identified several events with behaviors more consistent with benthic foraging where grouper were highly active while remaining at constant depth. As such, intensive foraging by multiple individuals may occur during more sporadic time periods. Grouper remained close to the seafloor as currents exceeded 0.4 m s-1 but moved up into the water column during cold-water incursions (<24°C). Abiotic conditions may limit vertical habitat use and could potentially influence spawning and foraging behavior. Multi-sensor telemetry combined with time-series analysis can be used to remotely measure individual behavior within spawning aggregations. The timing of these behaviors within the FSA may also have implications for the ecological role groupers play as predators and, potentially, in bottom-up processes.

An investigation on the collapse pressure prediction of subsea pipelines with realistic corrosion defects

Subsea pipelines are widely used for oil and gas transportation, but they are susceptible to failure due to corrosion. Corrosion in pipelines typically results in defects of varying depths and complex shapes. The computational simulation through the finite element (FE) method is one of the most efficient and accurate tools for assessing the integrity of corroded subsea pipes by allowing the simulation of the nonlinear behavior and assessing the hydrostatic collapse. This paper evaluates the collapse response of subsea pipelines with realistic corrosion defects. The study uses the PIPEFLAW system - developed by the PADMEC (High-Performance Processing on Computational Mechanics) research group from UFPE - which integrates reliable tools for automatic FE model generation and performs nonlinear analyses. After validation based on the experimental tests available in the literature, the effect of realistic corrosion defects on the collapse pressure of subsea pipelines is analyzed in detail. The results are compared to results obtained using a semi-empirical method and numerical results obtained considering idealized FE models, i.e., constant-depth and elliptical-shaped corrosion defects. It is observed that the non-uniformity of defects is an important factor affecting the collapse response of pipes. In addition, the idealized geometry of the corrosion defects, especially when considering constant depth, leads to an excessively conservative prediction of the hydrostatic collapse.

Joining of thin aluminum sheets by micro-friction stir welding (μFSW) using a pinless tool

Abstract In the present research, butt welding of 0.8 mm thick aluminum 6061–T6 sheets has been executed using a pinless tool with variable tool rotational speed (1000-2500 rpm), welding speed (100–250 mm min−1), and a constant plunging depth (0.1 mm). Tensile and microhardness tests have been conducted to evaluate the joint’s mechanical strength. The joint developed at 2500 rpm, and 100 mm min−1 shows a maximum strength of 277.65 MPa (88.4% of original strength), indicating that higher tool rotational speed and slower welding speed enhance joint formation through adequate heat generation and material intermixing. Small amount of defects like flash, surface galling, and irregular shoulder marks have been found in the weld region.

Effect of Interfacial Tension on Internal Waves in two Superposed Liquids against a Vertical Cliff

A simple and straightforward reduction method is described in this analysis to obtain the linear solution of the obliquely incident incoming waves towards a rigid vertical cliff in two superposed liquids. The Analytical expressions for the velocity potentials in each of the liquids are obtained considering the effect of interfacial tension where the lower liquid is of finite constant depth and the upper liquid is of finite constant height. Various known results are recovered as special cases of the general problem considered here.

Optimizing of machining parameters for Hypereutectic Aluminium Silicon Alloys A390 with minimum quantity lubrication in turning using vegetable-based nano fluids

Abstract Aluminium alloys are rapidly developing in response to regulatory and industry trends. The automotive industry’s push for lighter, more fuel-efficient vehicles has driven the fast-paced development and adoption of aluminium alloys, which have historically been regarded as the automotive production material with the fastest rate of growth. Parts made of aluminium alloys are significantly lighter than those made of steel, which can improve fuel efficiency and reduce emissions, making aluminium an environmentally friendly choice. The high silicon concentration in aluminium silicon alloys A390, which varies from 17 to 18% and has good casting qualities, affects the machinability process. In order to optimise machining settings and determine the aspects that most effect surface roughness, this study looks at the machinability performance, concentrating on the surface roughness of machined surfaces. The cutting parameters employed in this study were a constant depth of cut of 0.1 mm, a feed rate of 0.1 to 0.3 mm/min, and a cutting speed range of 300 to 900 m/min. The turning machining process was performed utilising nano-based silicon dioxide (SiO2)-based fluids combined with palm oil as a lubricant under minimal quantity lubricant (MQL) conditions. Next, a mathematical model was developed to predict outcomes, optimize processes, understand variable relationships, and save time and resources. The effect of machining parameters on surface roughness was investigated using the analysis of variance (ANOVA). The ANOVA revealed that feed rate and speed were important factors. The best settings for minimum quantity lubrication (MQL) were 900 m/min for the cutting speed and 0.1 mm/min for the feed rate. With these settings, 0.451 μm of minimised surface roughness was attained.

Towards sustainable machining: an experimental study of eco-friendly MQL and its impact on machinability and future opportunities

Abstract Enforcement of stricter environmental policies calls for alternative methods that could reduce the usage of cutting fluid during machining. Thus, dry machining and minimum quantity lubrication (MQL) machining are gaining practical importance. From this perspective, the development of new biodegradable MQL fluids and their performance assessment during machining is acquiring global attention. In this work, Jatropha crude oil (JCO) is chemically transformed into an epoxidized product and used as a MQL fluid. The turning experiments are conducted on Nimonic 80A under varying cutting speeds, and feed rates with constant depth of cut to examine the effects on machinability characteristics. The experiments are conducted under three different environments viz. dry, conventional minimum quantity lubrication (CMQL) and epoxidized minimum quantity lubrication (EMQL). The cutting force, tool flank wear, surface roughness and chip morphology are used as performance indicators. Regarding environmental concerns, the EMQL proved to be a viable substitute for CMQL as it demonstrated the lowest cutting force, tool wear and surface roughness. EMQL can reduce tool wear and surface roughness to the extent of about 54% and 22% as compared to the dry machining environment. The cutting force is reduced by about 13% and 34% by adopting CMQL and EMQL respectively even under the high feed (f = 0.45 mm min−1) condition. The sustainability assessment model developed using the Pugh matrix environmental approach disclosed EMQL system helps in attaining the desired machinability qualities while offering environmental friendliness and cleaner production.

Grey Relationship Analysis of Cutting Forces and Surface Roughness in Turning using Cryo-treated and Untreated Cutting Tools

The aim of this experimental study is to establish the optimum heat treatment procedure and machining parameters to obtain values of cutting force and surface roughness in machining AISI 1050 workpiece by utilizing grey relations analysis based on Taguchi method. In this regard, machining operations were carried out at three different cutting speeds and three different feed rates at a constant depth of cut. Taguchi mixed-level design L18 (2^2 3^2) was chosen for machining experiments. The optimum heat treatment and machining parameters for determination of cutting force and surface roughness values were identified according to the fact that higher the Signal/Noise ratio is better based on grey relations analysis of Taguchi method. The results showed that the optimum parameters for surface roughness and cutting forces were obtained as 0.1 mm/rev at feed rate and 180 m/min at cutting speed with cryo-treated cutting tool. According to ANOVA table and Signal/Noise ratios, it was specified that the most effective parameters on cutting forces and surface roughness were feed rate, cutting speed and heat treatment conditions, respectively.

Mechanisms of Increasing Weld Depth during Temporal Power Modulation in High‐Power Laser Beam Welding

Understanding the fundamental mechanisms of action for increasing weld depth during temporal power modulation in laser beam welding could allow dissimilar rotational welding without the introduction of concomitant turbulence, but with enhanced intermixing. The investigations are conducted on 30 mm‐diameter round bars of stainless steel alloy 1.4301 and nickel base alloy 2.4856 utilizing a 16 kW disk laser beam source. Modulation frequencies are 0/50/100/200 Hz at low, medium, and high amplitudes of laser beam power. The influence on the process and weld characteristics is investigated through high‐speed imaging with grayscale analysis, keyhole depth measurements, metallographic sections, and energy‐dispersive X‐ray spectroscopy analysis. The objectives are successfully achieved, and the underlying mechanism is maintaining the keyhole depth at a higher level for modulation frequencies of 200 Hz and a high amplitude of laser beam power, which is related to the keyhole inertia. Based on this, a novel welding mode with a constant keyhole depth is proposed. Furthermore, up to 20% increase in weld depth is achieved, a saturation limit for the modulation frequency is identified, intermixing within the weld is enhanced, and a model for predicting the weld depth based solely on measurements of the surface width is developed.

An Analytical Study of Tsunamis Generated by Submarine Landslides

In this work, the problem of tsunamis generated by underwater landslides is addressed. Two new solutions are derived in the framework of the linear shallow water equations and linear potential wave theory, respectively. Those solutions are analytical (1 + 1D) and another is semi-analytical (2 + 1D). The 1 + 1D model considers a solid body sliding over a sloping beach at a constant speed, and the 2 + 1D model considers a solid landslide that moves at a constant velocity on a flat bottom. The solution 1 + 1D is checked numerically using a different finite scheme. The 2 + 1D model examines the kinematic and geometric features of the landslide at a constant ocean depth and its influence on the generation of tsunamis. Landslide geometry significantly influences run-up height. Our results reveal a power law relationship between normalized run-up and landslide velocity within a realistic range and a negative power law for the landslide length–thickness. Additionally, a critical aspect ratio between the length and width of the sliding body is identified, which enhances the tsunamigenic process. Finally, the results show that the landslide shape does not have a decisive influence on the pattern of tsunami wave generation and propagation.

Improved Lower Bound, and Proof Barrier, for Constant Depth Algebraic Circuits

We show that any product-depth Δ algebraic circuit for the Iterated Matrix Multiplication polynomial IMM n, d (when d = O (log n /log log n ) must be of size at least \(n^{\Omega (d^{1/(\varphi ^2)^{\Delta }})}\) , where φ = 1.618 … is the golden ratio. This improves the recent breakthrough result of Limaye, Srinivasan, and Tavenas (FOCS’21), who showed a super polynomial lower bound of the form \(n^{\Omega (d^{1/4^{\Delta }})}\) for constant-depth circuits. One crucial idea of the (LST21) result was to use set-multilinear polynomials where each set in the variables’ underlying partition could be of different sizes. By picking the set sizes more carefully (depending on the depth we are working with), we first show that any product-depth \(\Delta\) set-multilinear circuit for \(\mathrm{IMM}_{n,d}\) (when \(d = O(\log n)\) ) needs size at least \(n^{\Omega (d^{1/\varphi ^{\Delta }})}\) . This improves the \(n^{\Omega (d^{1/2^{\Delta }})}\) lower bound of (LST21). We then use their Hardness Escalation technique to lift this to general circuits. We also show that these techniques cannot improve our lower bound significantly. For the specific two set sizes used in (LST21), they showed that their lower bound cannot be improved. We show that for any \(d^{o(1)}\) set sizes (out of maximum possible d ), the scope for improving our lower bound is minuscule. There exists a set-multilinear circuit that has product-depth \(\Delta\) and size almost matching our lower bound such that the value of the measure used to prove the lower bound is maximum for this circuit. This results in a barrier to further improvement using the same measure.

Initial Experimental Investigation of Hydraulic Characteristics at Right-Angle Diversion in a Combined Canal and Pipe Water Conveyance System

To enhance the efficiency of irrigation water utilisation, China is progressively converting irrigation ditches into pipelines. The water distribution outlets in irrigation zones are predominantly right-angled, and there are typically occurrences of erosion, sedimentation, and structural deterioration in the surrounding areas. This article employs a synthesis of indoor physical model experiments and theoretical analysis to examine the distribution of channel flow velocity and variations in water surface profile, pipeline flow rate, diversion ratio, circulation intensity, and turbulence energy across different relative water depths. The experimental results indicate that the water surface adjacent to the main canal wall demonstrates a pattern of initial decline, followed by an increase and subsequently another decline; furthermore, as the water level in the main channel rises, the magnitude of this fluctuation progressively diminishes. In some sections of the canal, the water surface elevation progressively increases, albeit with minimal amplitude. With a constant relative water depth, an increase in main channel flow results in a corresponding increase in pipeline flow; however, the diversion ratio is inversely related to the main channel flow. Conversely, when the main channel flow rate is constant, the diversion ratio increases as relative water depth rises. The vertical flow velocity near the water diversion outlet has a negative value, signifying the existence of a backflow zone, while the horizontal flow velocity varies considerably, facilitating the formation of circulation and resulting in localised deposition and erosion. The water flow near the pipe inlet downstream of the lower lip of 0.5 times the pipe diameter is impacted by the return zone, which has a higher turbulence energy and circulation strength and is more susceptible to siltation. The turbulence energy of the water flow is higher in the range of 0.5 times the pipe diameter upstream and downstream of the pipe inlet. This research is highly significant in facilitating the conversion of irrigation channels into pipelines.

Undular Bore Due to a Low Pressure or Bottom Trough Moving at the Critical Speed

AbstractA low pressure or bottom obstacle of negative displacement moves at the critical speed along a fluid layer of constant depth. The disturbance causes a depression of the surface at its forward position. The nonlinear dynamics generates a group of short waves attached to the disturbance. The number of two to six crests have a wavelength of 5.7–12 times the water depth. The wave height increases with the decreasing wavelength. The waves of the group do not follow the dispersion properties of cnoidal waves or Stokes waves. The group is rather characterised as an undular bore. The bore develops during a travel distance of 7–15 times the length of the disturbance. Its front eventually moves ahead of the driving disturbance where the leading crest develops into a solitary wave. A short disturbance is more powerful, but generates fewer crests compared to a long one. Comparison to the generation phase of upstream waves due to a high pressure (ship) or a bottom elevation shows that the wavelength in the two cases is approximately equal.

An Effective Water Depth Correction for Pressure-Based Wave Statistics on Rough Bathymetry

Abstract Near-bottom pressure sensors are widely used to measure surface gravity waves. Pressure spectra are usually converted to sea surface elevation spectra with a linear-theory transfer function assuming constant depth. This methodology has been validated over smooth sandy beaches but not over complex bathymetry of coral or rocky environments. Bottom-mounted pressure sensors collocated with wave buoys in 10–13-m water depth from a 5-week rocky shoreline experiment are used to quantify the error of pressure-based surface gravity wave statistics and develop correction methods. The rough bathymetry has O(1) m vertical variability on O(1–10) m horizontal scales, much shorter than the 90–40-m wavelength of sea band (0.1–0.2 Hz). For sensor stability, pressure sensors were deployed by divers in bathymetric lows. When using the local depth measured by the pressure sensor, significant wave height squared overestimates the direct wave buoy measurements (up to 21%) in the sea band. An effective depth hypothesis is proposed where a spatially averaged water depth provides more accurate wave height statistics than the local depth at the pressure sensor. An optimal depth correction, estimated by minimizing the wave height error, varies from 0.1 to 1.6 m. A bathymetry averaging scale of 13 m is found by minimizing the median bathymetry deviation relative to the optimal. The optimal and averaged bathymetry depth corrections are similar across locations and, using linear theory, significantly reduce wave statistical errors. Therefore, pressure-based wave measurements require a correction that depends on the spatially averaged bathymetry around the instrument. The larger errors when using the local depth suggest that approximately linear surface waves are not strongly modified by abrupt depth changes over O(1) m horizontal scales. Significance Statement The measurement of surface waves by bottom-mounted pressure sensors relies on wave theory formally derived for constant depth. We show that the constant depth assumption leads to systematic errors in wave statistics from observations over a rough, rocky bottom. By considering a spatially averaged bathymetry instead of the local water depth at the pressure sensor, the accuracy of wave energy density is improved, and upper-bound biases decay from 20% to 10%.