Dynamic machine foundations can be considered as a necessary component of the industrial infrastructure. Design of the dynamic equipment foundations has, however, traditionally been grounded on a rule of thumb that is inaccurate and rigid to use at the discretion of the engineers. The conventional rule of thumb, which includes minimum weight ratios and resonance avoidance criteria, has been used singularly with two poles, which can be either conservatively designed systems that are too heavy, or systems that are going to experience too much vibration and fatigue. This paper presents a novel, analytical framework for the reinterpretation of traditional design practices, using a physics-based approach, and results in a single, unified overall performance metric: the Combined Safety Index (CSI). The method utilizes frequency-dependent soil-foundation interaction models, allowing for a systematic evaluation of both inertially related and resonantly related stability under harmonic excitations. Using large-scale validations of real-world, global operational and geotechnical data from numerous case studies, including centrifugal compressors, blowers, and horizontal equipment, the reliability of the framework was demonstrated to be high (> 97%), with greater than 97% of the simulated designs meeting CSI ≥ 1.0. In addition, the method allows for mass optimization resulting in reductions in the amount of concrete used, and thus reductions in cost and environmental impact, of up to 45%. Unlike rule-of-thumb methods, this model allows designers to make informed decisions regarding the trade-off between the amount of mass of the foundation and detuning of the operating frequency, and thus supports economic efficiency and environmental sustainability. Statistical analyses, including local and global sensitivity analysis and Monte Carlo uncertainty quantification of the results, confirmed that the primary variables controlling system safety are the damping ratio (ζ) and the mass of the foundation (Wf). This work therefore provides practicing engineers with a practical, computationally efficient tool for designing safer, more sustainable foundations, and assists in advancing the state-of-the-art in design practice and in advancing digital engineering. © Springer Nature Switzerland AG 2026.
In this paper, three approximate methods namely the Bernoulli, the Bernstein, and the shifted Legendre polynomials operational matrices are presented to solve two important nonlinear ordinary differential equations that appeared in engineering and applied science. The Riccati and the Darcy-Brinkman-Forchheimer moment equations are solved and the approximate solutions are obtained. The methods are summarized by converting the nonlinear differential equations into a nonlinear system of algebraic equations that is solved using Mathematica®12. The efficiency of these methods was investigated by calculating the root mean square error (RMS) and the maximum error remainder (𝑀𝐸𝑅n) and it was found that the accuracy increases with increasi
... Show MoreThe effect of compound machine on wheat/ AlNoor cultivar was studied based on some technical indicators. were tested under three speeds ( 2.541, 3.433 and 4.091km.hr-1) and three tillage depths (14, 16 and 18cm). The experiments were conducted in a factorial experiment under complete randomized design with three replications. The results showed that the 2.541km.hr-1 practical speed was significantly better than other two speed in all studied conditions. Except for the FC, which achieved the best results with the third speed 4.091 km.hr-1. mechanical parameters, plant growth parameters and yield and growth parameters. The 1
Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th
... Show MoreThis paper presents an improved technique on Ant Colony Optimization (ACO) algorithm. The procedure is applied on Single Machine with Infinite Bus (SMIB) system with power system stabilizer (PSS) at three different loading regimes. The simulations are made by using MATLAB software. The results show that by using Improved Ant Colony Optimization (IACO) the system will give better performance with less number of iterations as it compared with a previous modification on ACO. In addition, the probability of selecting the arc depends on the best ant performance and the evaporation rate.
Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati
... Show MoreThe drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the
Lecture method is still need to a part of PBL in order to explain the difficult and abstract concepts in all fields of physics particularly thermodynamics. Introducing and promoting PBL in the lecture method is wise step for innovation in teaching and learning. The objective of this study is to compare the effects of using three methods: problem-based learning (PBL), PBL with lecture method, and conventional teaching on undergraduate physics students’ understanding of thermodynamics. The actual sample size comprises of 122 students, who were selected randomly from the Physics Department, College of Education in Iraq in the academic year 2011-2012. In this study, the pre- and post-test were done and the instruments were administered to the
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