Search Results (3,617)

The stop-hole technique is a well-known strategy to extend the fatigue life of cracked components. The ability to estimate fatigue life after the hole is important for safety reasons. The objective here is to develop strategies for the accurate prediction of initiation and propagation life ahead of the stop-hole. Experimental work was developed in a Compact-Tension (CT) specimen made of 7050-T7451 aluminium alloy and with a 3 mm diameter hole. A total number of 625,000 load cycles were required to re-initiate the crack after the hole. Crack initiation life after the hole was estimated using the Theory of Critical Distances combined with the Smith–Watson–Topper parameter. A value of a₀ = 31.83 µm was obtained for El Haddad parameter, which was used to define the critical distance. The predicted life was found to be only 4% lower than the experimental value. The fatigue crack growth (FCG) rate was calculated using a node release strategy, assuming that cyclic plastic deformation is the main damage mechanism and that cumulative plastic strain is the crack driving parameter. A good agreement was found between the numerical predictions of da/dN and the experimental results. The main result, however, is the proposed methodology, which allows predicting the initiation and propagation lives in notched components. Full article

Global recoverable shale gas reserves are estimated to be 214.5 × 10¹² m³. Estimation methods for shale gas resources, such as volumetric, analog, and genetic approaches, have been widely used in previous studies. However, these approaches have notable limitations, including the substantial effect of rock heterogeneity, difficulties in determining the similarity of analog accumulations, and unsuitability for evaluating high-mature–overmature source rocks. In the Qiongzhusi Formation (Є1q) of the Sichuan Basin, China, extensive development of high-mature–overmature shales has led to significant advancements in conventional and unconventional shale gas exploration. This progress highlights the need for the development of an integrated evaluation system for conventional and unconventional resources. Hence, this study uses the whole petroleum system theory and an improved hydrocarbon generation potential method to analyze the distribution patterns of hydrocarbon generation, retention, and expulsion during various stages of oil and gas accumulation in the Є1q. In addition, it assesses the resource potential of conventional and shale oil and gas. Hydrocarbon generation and expulsion centers are favorable exploration targets for conventional oil and gas, primarily located in the central and northern regions of the Mianyang—Changning rift trough, with an estimated resource potential of 6560 × 10¹² m³. Hydrocarbon retention centers represent promising targets for shale oil and gas exploration, concentrated in the central Mianyang—Changning rift trough, with a resource potential of 287 × 10¹² m³. This study provides strategic guidance for future oil and gas exploration in the Є1q and offers a methodological reference for integrated resource assessments of conventional and unconventional oil and gas systems of high-mature–overmature source rocks in similar basins worldwide. Full article

A constant proton relative biological effectiveness (RBE) of 1.1 for tumor control is currently used in proton therapy treatment planning. However, in vitro, in vivo and clinical experiences indicate that proton RBE varies with kinetic energy and, therefore, tissue depth within proton Bragg peaks. A number of published RBE models capture variations in proton RBE with depth. The published models can be sub-divided into empirical (or phenomenological) and biophysical (or mechanistic-inspired) RBE models. Empirical RBE models usually characterize the beam quality through the dose-averaged linear energy transfer (${\mathrm{LET}}_{\mathrm{D}}$), while most biophysical RBE models relate RBE to the dose-averaged lineal energy (${\mathrm{y}}_{\mathrm{D}}$). In this work, an analytic microdosimetry model and the Monte Carlo damage simulation code (MCDS) were utilized for the evaluation of the ${\mathrm{LET}}_{\mathrm{D}}$ and ${\mathrm{y}}_{\mathrm{D}}$ of monoenergetic proton beams in the clinically relevant energy range of 1–250 MeV. The calculated ${\mathrm{LET}}_{\mathrm{D}}$ and ${\mathrm{y}}_{\mathrm{D}}$ values were then used for the estimation of the RBE for five different cell types at three dose levels (2 Gy, 5 Gy and 7 Gy). Comparisons are made between nine empirical RBE models and two biophysical models, namely, the theory of dual radiation action (TDRA) and the microdosimetric kinetic model (MKM). The results show that, at conventional dose fractions (~2 Gy) and for proton energies which correspond to the proximal and central regions of the spread-out Bragg peak (SOBP), RBE varies from 1.0 to 1.2. At lower proton energies related to the distal SOBP, we find significant deviations from a constant $\mathrm{RBE}$ of 1.1, especially for late-responding tissues (low ${(\alpha /\beta )}_R$ of ~1.5–3.5 Gy) where proton RBE may reach 1.3 to 1.5. For hypofractionated dose fractions (5–7 Gy), deviations from a constant $\mathrm{RBE}$ of 1.1 are smaller, but may still be sizeable, yielding RBE values between 1.15 and 1.3. However, large discrepancies among the different models were observed that make the selection of a variable RBE across the SOBP uncertain. Full article

In this research, a feedback nonlinear control law was designed and tested to perform acquisition and station-keeping maneuvers for a lunar navigation constellation. Each satellite flies an Elliptical Lunar Frozen Orbit (ELFO) and is equipped with a steerable and throttleable low-thrust propulsion system. Lyapunov stability theory was employed to design a real-time feedback control law, capable of tracking all orbital elements (including the true anomaly), expressed in terms of modified equinoctial elements (MEEs). Unlike previous research, control synthesis was developed in the complete nonlinear dynamical model, and allows for driving the spacecraft toward a time-varying desired state, which includes correct phasing. Orbit propagation was performed in a high-fidelity framework, which incorporated several relevant harmonics of the selenopotential, as well as third-body effects due to the gravitational pull of the Earth and Sun. The control strategy at hand was successfully tested through two Monte Carlo campaigns in the presence of nonnominal flight conditions related to estimation errors of orbit perturbations, accompanied by the temporary unavailability and misalignment of the propulsive thrust. Full article

Sediment transport can be observed within the flow of water in rivers, canals, and coastal regions, encompassing both suspended-load transport and bed-load transport. Bed-load transport specifically occurs near the riverbed, playing a crucial role in the formation of the riverbed itself. The current study aimed to explore the process of sediment transport by employing the entropy concept as a theoretical approach. To this end, field data collected using a current meter in the Alaknanda River at Srinagar in India were utilized. A comparison was made between the calculated mean velocity and discharge values and the observed data obtained from the Central Water Commission (CWC), demonstrating a maximum error percentage of 9%. Subsequently, shear velocity was determined for various cross-sections under different flow scenarios. The Shields parameter was then derived from the shear-velocity distribution to evaluate the transport potential of the sediment particles. The model results showed varying bed-load transport rates that increased as the particle size decreased and the discharge rate increased. In conclusion, the study findings highlight the efficacy of utilizing the entropy theory for estimating flow discharge and sediment transport in developing countries. Full article

This paper investigates a consensus problem for a class of T–S fuzzy multiple-agent systems (MASs) with unknown input (UI). To begin with, an unknown input observer (UIO) is able to asymptotically estimate the system state and the UI is designed for each agent. In order to construct the UIO, the state interval estimation is obtained by first using zonotope theory. Next, using the interval estimation of the state, a correlation of the state and the UI is built. Subsequently, a UIO is constructed, which is proposed by building upon the algebraic relationship. Moreover, by using the estimations of the state and the UI, a distributed control protocol is developed based on the proposed UIO. And, with the proposed distributed control protocol, the T–S fuzzy MAS can achieve consensus, in that all the states of the agents can converge to the leader’s state asymptotically. Finally, the effectiveness of the proposed method is demonstrated through two simulation examples. Full article

This paper provides a study on optimal prediction problems in a linear model and its subsample models with linear stochastic restrictions, using matrix theory for precise analytical solutions. It focuses on deriving analytical expressions using block matrix inertia and rank methods to determine which of the best linear unbiased predictors (BLUPs) of a general vector of unknown parameters is superior to others under a stochastically restricted linear model and its subsample models. Additionally, this study examines the comparative results of the best linear unbiased estimators of unknown parameters. The comparisons in the study are based on the mean squared error matrix (MSEM) criterion. Finally, a numerical example is given to illustrate the theoretical results. Full article

This paper presents the development of an Active Disturbance Rejection Controller (ADRC) to address the trajectory tracking problem of a 2DOF (Degrees of Freedom) Serial Flexible Robot. The proposed approach leverages differential flatness theory to determine the system’s flat output, simplifying the trajectory tracking problem into a linear state feedback control with disturbance rejection. A set of a Generalized Proportional Integral Observer (GPIO) and Luenberger observers is employed to estimate the derivatives of the flat output and both internal and external disturbances in real time. The control law is experimentally validated on a 2DOF Serial Flexible Robot prototype developed by Quanser. Quantitative results demonstrate that the ADRC achieves superior performance compared to a partial state feedback control scheme, with a Mean Squared Error (MSE) as low as 1.0651 × 10⁻⁵ rad² for trajectory tracking. The ADRC effectively suppresses oscillations, minimizes high-frequency noise and reduces saturation effects, even under external disturbances. These findings underscore the robustness and efficiency of the proposed method for underactuated flexible systems. Full article

Cisplatin-based platinum compounds are important clinical chemotherapeutic agents that participate in most tumor chemotherapy regimens. Through density-functional theory calculations, the formation and stability of the inorganic oxide carrier, the mechanisms of the hydrolysis reaction of the activated platinum compound, and its binding mechanism with DNA bases can be studied. The higher the oxidation state of Pt (II to IV), the more electrons transfer from the magnesia–gold composite material to the platinum compound. After adsorption on the composite carrier, 5d←2p coordination bonds of Pt-N are strengthened. For flat and oblique adsorption modes of cisplatin, there is no significant difference in the density of states of the gold and magnesium oxide film, indicating the maintenance of the heterojunction structural framework. However, there are significant changes in the electronic states of cisplatin itself with different adsorption configurations. In the flat configuration, the band gap width of cisplatin is larger than that of the oblique configuration. The Cl-Pt bond range in the Pt(III) compound shows a clear charge reduction on the magnesia film, indicating the Cl-Pt bond is an active site with the potential for decomposition and hydrolysis. The substitution of chloride ions by water can lead to hydrolysis products, enhancing the polarization of the composite and showing strong charge separation. The hydrolysis of the free platinum compound is endothermic by 0.309 eV, exceeding the small activation energy barrier of 0.399 eV, indicating that hydrolysis of this platinum compound is easily achievable. ADME (absorption, distribution, metabolism, and excretion) prediction parameters indicate that hydrolysis products have good ESOL (Estimated SOLubility) solubility and high gastrointestinal absorption, consistent with Lipinski’s rule. During the coordination reaction process, there are significant changes in the distribution of frontier molecular orbitals, with the HOMO (highest occupied molecular orbital) of the initial state primarily located on the purine base, providing the possibility for electron transfer to the empty orbitals of the platinum compound in the LUMO (lowest unoccupied molecular orbital). The HOMO and HOMO-1 of the transition state and product are mainly distributed on the platinum compound, indicating clear electron transfer and orbital rearrangement. The activation energy barrier for the purine coordination reaction with the hydrolysis products is reduced to 0.61 eV, and the dipole moment gradually decreases to 6.77 Debye during the reaction, indicating a reduction in the system’s charge separation and polarization. This contribution is anticipated to provide a new theoretical clue for developing inorganic oxide carriers of platinum compounds. Full article

Autonomous technologies have revolutionized transportation, military operations, and space exploration, necessitating precise localization in environments where traditional GPS-based systems are unreliable or unavailable. While widespread for outdoor localization, GPS systems face limitations in obstructed environments such as dense urban areas, forests, and indoor spaces. Moreover, GPS reliance introduces vulnerabilities to signal disruptions, which can lead to significant operational failures. Hence, developing alternative localization techniques that do not depend on external signals is essential, showing a critical need for robust, GPS-independent localization solutions adaptable to different applications, ranging from Earth-based autonomous vehicles to robotic missions on Mars. This paper addresses these challenges using Visual odometry (VO) to estimate a camera’s pose by analyzing captured image sequences in GPS-denied areas tailored for autonomous vehicles (AVs), where safety and real-time decision-making are paramount. Extensive research has been dedicated to pose estimation using LiDAR or stereo cameras, which, despite their accuracy, are constrained by weight, cost, and complexity. In contrast, monocular vision is practical and cost-effective, making it a popular choice for drones, cars, and autonomous vehicles. However, robust and reliable monocular pose estimation models remain underexplored. This research aims to fill this gap by developing a novel adaptive framework for outdoor pose estimation and safe navigation using enhanced visual odometry systems with monocular cameras, especially for applications where deploying additional sensors is not feasible due to cost or physical constraints. This framework is designed to be adaptable across different vehicles and platforms, ensuring accurate and reliable pose estimation. We integrate advanced control theory to provide safety guarantees for motion control, ensuring that the AV can react safely to the imminent hazards and unknown trajectories of nearby traffic agents. The focus is on creating an AI-driven model(s) that meets the performance standards of multi-sensor systems while leveraging the inherent advantages of monocular vision. This research uses state-of-the-art machine learning techniques to advance visual odometry’s technical capabilities and ensure its adaptability across different platforms, cameras, and environments. By merging cutting-edge visual odometry techniques with robust control theory, our approach enhances both the safety and performance of AVs in complex traffic situations, directly addressing the challenge of safe and adaptive navigation. Experimental results on the KITTI odometry dataset demonstrate a significant improvement in pose estimation accuracy, offering a cost-effective and robust solution for real-world applications. Full article

Skid-steer mobile robots (SSMRs) are ubiquitous in indoor and outdoor applications. Their accurate trajectory tracking control is quite challenging due to the uncertainties arising from the complex behavior of frictional force, external disturbances, and fluctuations in the instantaneous center of rotation (ICR) during turning maneuvers. These uncertainties directly disturb velocities, hindering the robot from tracking the velocity command. This paper proposes a nonsingular terminal sliding mode control (NTSMC) based on backstepping for a four-wheel SSMR to cope with the aforementioned challenges. The strategy seeks to mitigate the impacts of external disturbances and model uncertainties by developing an adaptive law to estimate the integrated lumped outcome. The finite time stability of the closed-loop system is proven using Lyapunov’s theory. The designed NTSMC input is continuous and avoids noticeable chattering. It was noted in the simulation analysis that the proposed control strategy is strongly robust against disturbance and modeling uncertainties, demonstrating effective trajectory tracking performance in the presence of disturbance and modeling uncertainties. Full article

Land degradation issues and declining fertility are driving the need for agroecological practices. This research analysed the determinants of acceptance and actual use of five main agroecological practices (contour farming techniques, organic fertiliser, crop association, improved seeds and integrated crop management practices) by farmers in Mali. The extended Unified Theory of Acceptance and Use of Technology (UTAUT) was used to develop the conceptual model. Data were collected from 505 randomly selected farming households in the cotton and cereal production zones in Mali. Partial Least Square–Structural Equation Modelling (PLS-SEM) was used to estimate technology acceptance and use. The findings revealed that behavioural intention is significantly and positively influenced by the expected performance and social influence. The expected effort is a key influential factor of the behavioural intention to adopt organic fertiliser. Experience has a mediating effect on the relationship between social influence and behavioural intention to adopt improved seeds adapted to the agroecological conditions. The actual use behaviour is directly and positively affected by the behavioural intention, facilitating conditions and expected net benefit. These findings align with the UTAUT model, have useful implications for both farmers and decision-makers and offer directions for technical approaches to agroecological practices’ development. Full article

Phenothiazine-based photosensitizers bear the intrinsic potential to substitute various expensive organometallic dyes owing to the strong electron-donating nature of the former. If coupled with a strong acceptor unit and the length of N-alkyl chain is appropriately chosen, they can easily produce high efficiency levels in dye-sensitized solar cells. Here, three novel D-A dyes containing 1H-tetrazole-5-acrylic acid as an acceptor were synthesized by varying the N-alkyl chain length at its phenothiazine core and were exploited in dye-sensitized solar cells. Differential scanning calorimetry showed that the synthesized phenothiazine derivatives exhibited behavior characteristic of molecular glasses, with glass transition and melting temperatures in the range of 42–91 and 165–198 °C, respectively. Based on cyclic and differential pulse voltammetry measurements, it was evident that their lowest unoccupied molecular orbital (LUMO) (−3.01–−3.14 eV) and highest occupied molecular orbital (HOMO) (−5.28–−5.33 eV) values were fitted to the TiO₂ conduction band and the redox energy of I⁻/I₃⁻ in electrolyte, respectively. The experimental results were supported by density functional theory, which was also utilized for estimation of the adsorption energy of the dyes on the TiO₂ and its size. Finally, the compounds were tested in dye-sensitized solar cells, which were characterized based on current–voltage measurements. Additionally, for the compound giving the best photovoltaic response, the efficiency of the DSSCs was optimized by a photoanode modification involving the use of cosensitization and coadsorption approaches and the introduction of a blocking layer. Subsequently, two types of tandem dye-sensitized solar cells were constructed, which resulted in an increase in photovoltaic efficiency to 6.37%, as compared to DSSCs before modifications, with a power conversion value of 2.50%. Full article

Heywood cases and other improper solutions occur frequently in latent variable models, e.g., factor analysis, item response theory, latent class analysis, multilevel models, or structural equation models, all of which are models with response variables taken from an exponential family. They have important consequences for scoring with the latent variable model and are indicative of issues in a model, such as poor identification or model misspecification. In the context of the 2PL and 3PL models in IRT, they are more frequently known as Guttman items and are identified by having a discrimination parameter that is deemed excessively large. Other IRT models, such as the newer asymmetric item response theory (AsymIRT) or polytomous IRT models often have parameters that are not easy to interpret directly, so scanning parameter estimates are not necessarily indicative of the presence of problematic values. The graphical examination of the IRF can be useful but is necessarily subjective and highly dependent on choices of graphical defaults. We propose using the derivatives of the IRF, item Fisher information functions, and our proposed Item Fraction of Total Information (IFTI) decomposition metric to bypass the parameters, allowing for the more concrete and consistent identification of Heywood cases. We illustrate the approach by using empirical examples by using AsymIRT and nominal response models. Full article

Developing theory-informed standard operating procedures (SOPs) for the continuous crystallisation of pharmaceuticals still remains a bottleneck. For the continuous manufacturing of pharmaceuticals, the current methods rely on the laborious trial-and-error approach to identify process conditions such as the dilution rate (flow per unit volume of reactor) and initial supersaturation, where the productivity will be at maximum at steady-state conditions. This approach, while proven and considered to be useful, lacks or ignores the information obtained from batch kinetics. Herein for the first time, we propose a theoretical method to develop batch kinetics-informed theoretical procedures for the continuous manufacturing of a model compound curcumin in isopropanol. The theoretical approach uses batch kinetic constants to theoretically identify the optimum dilution rate and the corresponding mass of the model compound curcumin when crystallised, as well as its productivity at steady-state conditions as a function of initial supersaturation. The theory-informed procedures will serve as a valuable guideline to develop operating procedures for the continuous production of the target compound and thus eliminate the trial-and-error approach used to develop the protocols for the continuous manufacturing of pharmaceuticals. We also showed that our methods allow for the estimation of the dilution rate that corresponds to washout conditions (i.e., where all the crystals in the crystalliser will be washed out due to the high flow rate of the input stream) during the continuous manufacturing of crystals. Full article