Modal Approach Research Articles

Reduced-Order Modeling of Steady and Unsteady Flows with Deep Neural Networks

Large-eddy and direct numerical simulations generate vast data sets that are challenging to interpret, even for simple geometries at low Reynolds numbers. This has increased the importance of automatic methods for extracting significant features to understand physical phenomena. Traditional techniques like the proper orthogonal decomposition (POD) have been widely used for this purpose. However, recent advancements in computational power have allowed for the development of data-driven modal reduction approaches. This paper discusses four applications of deep neural networks for aerodynamic applications, including a convolutional neural network autoencoder, to analyze unsteady flow fields around a circular cylinder at Re = 100 and a supersonic boundary layer with Tollmien–Schlichting waves. The autoencoder results are comparable to those obtained with POD and spectral POD. Additionally, it is demonstrated that the autoencoder can compress steady hypersonic boundary-layer profiles into a low-dimensional vector space that is spanned by the pressure gradient and wall-temperature ratio. This paper also proposes a convolutional neural network model to estimate velocity and temperature profiles across different hypersonic flow conditions.

Organizational culture archetypes and firm performance

Much of the research on organizational culture has been driven by the assumption that culture is associated with organizational performance. Surprisingly, the evidence for this linkage is ambiguous for two understandable reasons. First, there has been a proliferation of definitions and measures of the construct itself which has made aggregation of findings across studies confusing. Second, demonstrating that culture affects objective firm performance requires large cross-organizational samples—but the modal approach to measuring culture using surveys or qualitative research has made this difficult. Using a natural language processing measure of culture with a sample of 309 large U.S. companies, we show how (1) the norms and values that define culture may be understood as representing three underlying cultural archetypes (performance-orientation, people, and customers) and (2) that these archetypes are related to objective firm performance in understandable ways. We discuss the implications of these findings for future research on organizational culture.

Robust brain tumor classification by fusion of deep learning and channel-wise attention mode approach

Diagnosing brain tumors is a complex and time-consuming process that relies heavily on radiologists’ expertise and interpretive skills. However, the advent of deep learning methodologies has revolutionized the field, offering more accurate and efficient assessments. Attention-based models have emerged as promising tools, focusing on salient features within complex medical imaging data. However, the precise impact of different attention mechanisms, such as channel-wise, spatial, or combined attention within the Channel-wise Attention Mode (CWAM), for brain tumor classification remains relatively unexplored. This study aims to address this gap by leveraging the power of ResNet101 coupled with CWAM (ResNet101-CWAM) for brain tumor classification. The results show that ResNet101-CWAM surpassed conventional deep learning classification methods like ConvNet, achieving exceptional performance metrics of 99.83% accuracy, 99.21% recall, 99.01% precision, 99.27% F1-score and 99.16% AUC on the same dataset. This enhanced capability holds significant implications for clinical decision-making, as accurate and efficient brain tumor classification is crucial for guiding treatment strategies and improving patient outcomes. Integrating ResNet101-CWAM into existing brain classification software platforms is a crucial step towards enhancing diagnostic accuracy and streamlining clinical workflows for physicians.

CryoEM grid preparation: a closer look at advancements and impact of preparation mode and new approaches.

Sample preparation can present a significant hurdle within single particle cryo-electron microscopy (cryoEM), resulting in issues with reproducibility, data quality or an inability to visualise the sample. There are several factors which can influence this, including sample or buffer composition, grid type, route of sample preparation and interactions with the air-water interface (AWI). Here, we review some of the current routes for sample preparation and the associated challenges. We discuss a range of approaches for overcoming these challenges, such as minimising the grid preparation time, surfactants, grid type and biochemical approaches such as nanomagnetic beads. Finally, we discuss how a set of commercially available protein samples may serve as a benchmark suite for future technologies. This provides a route to compare techniques' abilities not just to generate high-resolution structures but also to overcome the challenges traditionally associated with cryoEM. As the field continues to produce new approaches to sample preparation and we start to better understand the underlying principles behind the behaviour of proteins within a thin film and in response to different environments, especially grid composition, it is hoped that more universal solutions can be provided that make the intractable systems tractable, improve resolution and, importantly, speed up data collection and reduce the currently required dataset sizes.

Flexible Colon Polyp Detection: A Dual Mode Approach for Detection and Segmentation of Colon Polyps with Optional Inpainting for Specular Highlight Mitigation

Flexible Colon Polyp Detection: A Dual Mode Approach for Detection and Segmentation of Colon Polyps with Optional Inpainting for Specular Highlight Mitigation

Transverse cracking signal characterization in CFRP laminates using modal acoustic emission and digital image correlation techniques

The process of formation and subsequent propagation of transverse cracks in 90° plies of carbon-fiber laminated composites was studied using modal acoustic emission approach and digital image correlation techniques. The results from modal acoustic emission approach, which included a newly developed processing tool for acoustic emission waveforms, provided information for identification and subsequent characterization or localization of signals originating from transverse cracking by analysis of the separated flexural and extensional Lamb wave modes in terms of their modal parameters. The digital image correlation method served as a verification tool of the acoustic emission data outputs in the terms of activity of significant localized events originating from the formation of the transverse crack in the 90oply. This made it possible to specify more locally the accompanying activity belonging to the formation or propagation of the magistral transverse crack. The manuscript also presents results related to the evolution of flexural/extensional wave modal parameters as the function of loading force for both [0/0/0/90]S and [90/0/0/0]S panels. It can be concluded that the detection of transverse cracks requires the need for applying a more complex acoustic emission data analysis methodology, while the standard parametric analysis, including the waveform peak frequency, is not sufficient. The presented methodology may serve as a basis for development of robust analysis tool capable of detecting the investigated phenomena.

VI—Four Grades of Modal Naturalism

Abstract How, if at all, can scientific progress improve our view of the modal facts? According to rationalist approaches to modal epistemology, science has no substantive role: a priori reflection reveals the structure of modal space, and a posteriori science merely locates us within that modal space, by identifying the actual properties and structures instantiated at our world. According to modal naturalist approaches, science provides evidence about the structure of the underlying modal space. In this paper I distinguish four versions of modal naturalism, with science playing an increasingly robust evidential role, and discuss their plausibility.

Stress stiffening effects in flexible Earth observation satellites with spinning appendage

Modern satellites often adopt innovative configurations to meet the escalating requirements of space operations. This study specifically focuses on one such configuration, exemplified by an Earth observation spacecraft equipped with a large rotating payload connected to the main bus through a flexible boom. The rotational motion of the payload is designed to extend the scanned area, resulting in a substantial reduction in the time required to complete a set of measurements, thus enhancing the overall performance. However, this configuration introduces greater complexity both in the analysis of the dynamical behavior and in the design of the control architecture. When dealing with flexible structures subject to rotational motion, as in this scenario, the stiffening effect resulting from inertial loads—particularly the centrifugal action—becomes crucial. In this study, we derive the dynamic equations of the multibody flexible spacecraft using Kane's formulation, which provides a streamlined set of ordinary differential equations by simplifying their derivation. Treating the link as an elastic beam, flexibility is incorporated through a modal decomposition approach that considers nonlinear elastic dynamics, ensuring the inclusion of stress stiffening in the dynamical model. Stress stiffening emerges as a fundamental effect in spinning space structures, where the contribution of the centrifugal force is significant. Incorrect predictions and structural instability for high spinning rates are observed when this effect is neglected. Furthermore, the error associated with overlooking this physical phenomenon is found to be dependent on the spinning rate. We identify kinematical conditions that render this effect negligible in relation to the fundamental deformation frequencies of the space system. Several numerical results are presented and discussed.

Modal approach to the dynamics of string instruments over the audible range

The present theoretical analysis addresses the dynamics of the bow instruments in the whole audible range of frequencies. Several scenarios are considered for the string-bridge-soundbox system: natural vibrations and frequency spectrum, external periodic excitation on some bridge point, and vibration induced by the bow rubbing. The single parts of the musical artifact are conveniently modelled and the bridge interfacing between the strings and the top plate of the soundbox is studied considering two possible vibrating modes of the bridge: a translational mode along its symmetry axis and a rotational mode around the waist centre. The bridge mechanical model is thus definable from both the kinematical and the dynamical aspects, and the relations between the forces and displacements of the strings and the sound box are formulated.The coupled natural modes of vibration are obtained in non-dissipative conditions, finding that the whole frequency spectrum is roughly given by the union of the uncoupled spectra, of the strings and the harmonic box. Then, introducing some level of dissipation, the frequency response to a transverse harmonic excitation on an arbitrary bridge point and the admittance on another arbitrary point of the instrument are studied, obtaining a useful tool to identify or verify the mechanical characteristics of the system. At last, the response to the bow excitation is analysed introducing an appropriate model for the nonlinear stick-slip contact between the bow and the strings and solving the motion equations by modal decomposition.

Impact of Low Freestream Turbulence and Surface Roughness on the Flat-Plate Boundary Layer Transition Under a High-Lift Airfoil Pressure Gradient

Abstract Effects of low incoming freestream turbulence level (Tu < 1%) and surface roughness on the transition of flat-plate boundary layers under a high-lift airfoil pressure gradient have been investigated. Time-resolved streamwise and wall-normal velocity fields with surface roughness values of Ra/C = 0.065 × 10−5, 4.417 × 10−5, and 7.428 × 10−5 have been measured at a fixed Reynolds number of 5.2 × 105 and freestream turbulence intensity of 0.2%. For the reference smooth surface of Ra/C = 0.065 × 10−5, a laminar separation bubble forms from about 64% to 83% of the chord length. Increasing surface roughness has little impact on the laminar boundary layer separation onset but reduces the height and length of the separation bubble and induces earlier transition. For Ra/C = 4.417 × 10−5, displacement thickness during transition is slightly thinner and the overall momentum deficit is slightly lower than those for Ra/C = 0.065 × 10−5. For Ra/C = 7.428 × 10−5, the separation bubble becomes hardly visible as the transition mode approaches the attached mode, and turbulent mixing by the wall-bounded turbulence becomes dominant. In addition, the portion of turbulent wetted area increases due to earlier transition, and momentum deficit increases more rapidly in the turbulent wetted area. Thus, the overall momentum deficit for Ra/C = 7.428 × 10−5 is larger than that for Ra/C = 0.065 × 10−5.

Evaluation of High Yielding Groundnut Varieties for North Transitional Zone of Karnataka State, India

Groundnut (Arachishypogaea L.) is an important oil seed crop grown in the arid andsemi-aridtropics of India under rainfed condition. The productivity is around 800 kg ha-1 in Karnataka as against national productivity of 1500 kg ha-1. The reasons for low productivity are many among them lack of improved variety in groundnut cultivation. Hence, study conducted to evaluate the high yielding groundnut varieties on farmers filed under farmers participatory mode approach. On field 25 FLD’s were planned by AICRP on Groundnut, MARS, UAS, Dharwad, Karnataka on farmers’ participatory mode approach under National Mission on Oilseeds and Oil Palm(NMOOP) programme and were conducted during kharif2021 with 25 farmers from Dharwad district. Each farmers field was considered as replication (25 no.) with 5 varieties as treatments and data was analysed statistically using Randomized complete block design. Statistical significance was tested with F test at 5 per cent level of probability. The study revealed that Dh-256(2850 kg ha-1) and K-1812 (Kadri Lepaxi) (2745 kg ha-1) recorded statistically on far dry pod yield. However, Dh-256 numerically out yielded K-1812 to the extent of 105 kg ha-1. Haulm yield when compared to the other varieties. A significant reduction in stem rot incidence was observed with respect to Dh-256(3.5%), K-1812(3.8%), G2-52(4.5%) and GPBD-4(4.7%) when compared to JL-24(8.1%) which resulted significant reduction plant population of JL-24 at harvest though it was having higher harvest index. The additional cost of cultivation of Rs. 2000 was spent on JL-24 to manage foliar diseases. Significantly higher gross returns were of Rs.148405 ha-1 and Rs.143460 ha-1, respectively by cultivating Dh-256 and K-1812 as against Rs.115740 ha-1 and Rs. 98728 ha-1 of local improved popular variety GPBD-4 and farmers check variety JL-24, respectively. From the results, farmers were very satisfied with Dh-256 and K-1812 newly released varieties of UAS, Dharwad, Karnataka and ARS, Kadiri, Andhra Pradesh. During, kharif2021, groundnut crop growth season was normal (496 mm from South West Monsoon i.e., June to September) for the Dharwad district and it was 4% higher than normal rainfall of 479 mm for the same period in the region, Further, groundnut crop not suffered due to dry spell any point of its growing period.

Optimizing Energy Consumption in 5G HetNets: A Coordinated Approach for Multi-Level Picocell Sleep Mode with Q-Learning

Cell standby, particularly picocell sleep mode (SM), is a prominent strategy for reducing energy consumption in 5G networks. The emergence of multi-state sleep states necessitates new optimization approaches. This paper proposes a novel energy optimization strategy for 5G heterogeneous networks (HetNets) that leverages macrocell-picocell coordination and machine learning. The proposed strategy focuses on managing the four available picocell sleep states. The picocell manages the first three states using the Q-learning algorithm, an efficient reinforcement learning technique. The associated macrocell based on picocell energy efficiency controls the final, deeper sleep state. This hierarchical approach leverages localized and network-wide control strengths for optimal energy savings. By capitalizing on macrocell-picocell coordination and machine learning, this work presents a promising solution for achieving significant energy reduction in 5G HetNets while maintaining network performance.

A high-precision 3D reconstruction method for the internal structure of small Solar System bodies

Small Solar System bodies (SSSBs) hold crucial information for understanding the formation and evolution of the Solar System. However, due to their considerable distance, small size, fast rotation, and a lack of prior information, the detection of these celestial bodies, especially their internal structures, faces numerous challenges. We explore whether the 3D structure of SSSBs can be reconstructed using monostatic radar. We investigated a more convenient observation mode and addressed the issue of the poor imaging quality of internal structures within existing imaging algorithms. Our study focused on a high-precision 3D imaging method for the internal structure of SSSBs based on radar signals. First, we considered a flyby observation mode that uses the spinning characteristics of the target for global observations, and we set up a scaled-down experimental system in the laboratory to simulate this observation mode. Next, we constructed a 3D printed physical surface model based on the shape of the asteroid 162173 Ryugu. We filled it with sand and inserted a small bottle containing different materials separately to construct two distinct layered analogs. The analogs were employed in laboratory measurements to acquire radar echoes, which were then inverted using both a classic back-projection (BP) algorithm and a modified multilayer back-projection (MLBP) method. The results shown that the 3D surface structure of the target can be reconstructed well through the BP and MLBP algorithms. The MLBP algorithm exhibits a higher reconstruction accuracy for internal structures. Moreover, compared to the BP method, the MLBP method is less sensitive to the quality of echo signals, resulting in a relatively stable imaging performance. Our findings reveal that observing and reconstructing the high-precision structure of SSSBs is feasible through our proposed method. The observation mode, experimental setup, and analog modeling approach are widely applicable and can be applied in future research on the detection of SSSBs with more diverse and complex structures.

The Specificity of Fantasy and the “Affective Novum”: A Theory of a Core Subset of Fantasy Literature

This article proposes a new approach to the nature of a core set within fantasy fiction that regards it as a speculative literature of the exploration of subjectivity, one which at its limit conjectures fresh possibilities for the subjective world. To motivate acceptance of this proposed approach, I begin by surveying the existing state of debate in the critical field. I notice the emergence of widening agreement on the idea that fantasy is a literature of the impossible. I then develop the logical implications of this widening agreement in the critical field, arguing that it entails a representational definition of fantasy literature, which implies a modal approach to the core set that defines this literary order. I suggest that the marvellous mode, the kind of writing which represents the impossible, is a broad class that includes other speculative literatures, and that what differentiates these is the referential world within which the impossible happens. The aim here is to break up monolithic conceptions of the impossible, while pointing to a motivation for developing an understanding of the specificity of a core set of fantasy texts that proceeds by way of contrasts. After explaining why I am extremely skeptical about the definition of science fiction as a “literature of the possible”, I probe descriptions of the difference between fantasy and sci-fi. I propose that whereas some science fiction is a literature of conjectural objectivity, guided by the “cognitive novum”, a significant group of fantasy texts is a literature of speculative subjectivity, guided by an “affective novum”.

Mathematical Modelling for Failure Analysis of Composite Drive Shaft Using Modal Flexibility and Curvature Method

Early damage identification in composite structures has attracted a lot of attention in post-failure examinations in recent years. In the research, torsional fatigue test of composite drive shafts has been done and numerical methodologies have been employed for the validation for premature failure using modal flexibility and modal curvature methods. Initially, the eigenvalue and eigenvectors of healthy and fractured drive shafts are evaluated using a numerical model and verified by fatigue experimental approach. Flexibility variance and the absolute curvature difference between the drive shafts that are fractured and those that are healthy are evaluated after mass normalization. Variations in absolute modal curvatures and variations in local flexibilities that are utilized to identify the existence, location, and severity of a drive shaft fracture. The position and severity of the fracture are predicted more precisely by the modal curvature approach than by the modal flexibility approach.

Active vibration control for flexible towers based on displacement observation and reduced-order controller in modal space: Theory and experiment

Active vibration control is not only suitable but also urgently needed in order to mitigate excessive vibration for dynamic systems such as wind turbine towers. However, there is a challenge of directly observing displacement and developing an efficient reduced-order control strategy. With this in view, a reduced-order controller based on displacement observation is developed for the vibration mitigation of flexible high towers, where the problems of low signal-to-noise ratio (SNR) and intricate acceleration-based control algorithms are eliminated completely. The displacement can be measured by laser or modern videometrics technology. A reduced-order model with an active mass damper (AMD) at the top of the tower is created using modal truncation approach based on modal participation factor (MPF), which successfully preserves the dominant modes of the original structure, and reduces the influence of high-frequency uncertainties. Considering structure uncertainties caused by environmental factors and aging process, an unscented Kalman filter (UKF) is introduced to identify the modal stiffness of the reduced-order model. The present study, using a 5 MW onshore wind turbine as an example, investigates active vibration control under wind and seismic loads and compares it with traditional tuned mass damper (TMD). From a dynamic perspective, the simplified model of wind turbine tower takes the form of a multi-degree-of-freedom series model. Consequently, a six-story steel frame platform has been constructed to experimentally validate the efficacy of the reduced-order controller. According to numerical simulation and laboratory testing, the control effect of the reduced-order controller with a few displacement states as feedback can be utilized as an active control strategy for high-rise flexible towers.

Deep tomography for the three-dimensional atmospheric turbulence wavefront aberration

Multiconjugate adaptive optics (MCAO) can overcome atmospheric anisoplanatism to achieve high-resolution imaging with a large field of view (FOV). Atmospheric tomography is the key technology for MCAO. The commonly used modal tomography approach reconstructs the three-dimensional atmospheric turbulence wavefront aberration based on the wavefront sensor (WFS) detection information from multiple guide star (GS) directions. However, the atmospheric tomography problem is severely ill-posed. The incomplete GS coverage in the FOV coupled with the WFS detection error significantly affects the reconstruction accuracy of the three-dimensional atmospheric turbulence wavefront aberration, leading to a nonuniform aberration detection precision over the whole FOV. We propose an efficient approach for achieving accurate atmospheric tomography to overcome the limitations of the traditional modal tomography approach. We employed a deep-learning-based approach to the tomographic reconstruction of the three-dimensional atmospheric turbulence wavefront aberration. We propose an atmospheric tomography residual network (AT-ResNet) that is specifically designed for this task, which can directly generate wavefronts of multiple turbulence layers based on the Shack-Hartmann (SH) WFS detection images from multiple GS directions. The AT-ResNet was trained under different turbulence intensity conditions to improve its generalization ability. We verified the performance of the proposed approach under different conditions and compared it with the traditional modal tomography approach. The well-trained AT-ResNet demonstrates a superior performance compared to the traditional modal tomography approach under different atmospheric turbulence intensities, various turbulence layer distributions, higher-order turbulence aberrations, detection noise, and reduced GSs conditions. The proposed approach effectively addresses the limitations of the modal tomography approach, leading to a notable improvement in the accuracy of atmospheric tomography. It achieves a highly uniform and high-precision wavefront reconstruction over the whole FOV. This study holds great significance for the development and application of the MCAO technology.

Causal relationships between gut microbiota and lymphoma: a bidirectional Mendelian randomization study.

Multiple studies have suggested a possible connection between the gut microbiota and the development of lymphoma, though the exact nature of this relationship remains unclear. This study aimed to explore whether a causal association exists between gut microbiota and lymphoma. A bidirectional two-sample Mendelian randomization (MR) approach was conducted to investigate potential causal effects between gut microbiota and various lymphoma subtypes. The primary method employed for MR analysis was inverse variance weighted (IVW), supplemented by additional methods including MR-Egger, weighted median, and weighted mode approaches. The Cochrane Q test, MR-PRESSO global test and MR-Egger intercept test were performed to assess pleiotropy and heterogeneity. Furthermore, a reverse MR analysis was performed to explore potential reverse causal effect. The primary MR analysis identified 36 causal relationships between genetic liabilities in gut microbiota and different lymphoma subtypes. Neither the MR-PRESSO test nor the MR-Egger regression detected any pleiotropy, and Cochran's Q test indicated no significant heterogeneity. Our MR analysis revealed substantial causal associations between gut microbiota and lymphoma, offering new insights into lymphoma prevention and management microbiota.

A Single-Center Experience in Combined Oncological-Surgical Treatment for Resectable Locally Advanced Non-Small Cell Lung Cancer (NSCLC).

Non-small cell lung cancer (NSCLC) is the most common pulmonary malignancy, frequently diagnosed at an advanced stage (III/IV). Patients in the Locally Advanced Stage Subgroup (IIIA) are relatively few, yet compose heterogenic phenotypes, posing a diagnostic and treating challenge, leading to a lack of clinical guidelines regarding the optimal standard of care. Several approaches exist, with a general agreement that a combined oncological and surgical modality approach is required. In this current retrospective descriptive study, patients with operable stage IIIA NSCLC who underwent surgery between 2013 and 2020 were evaluated on several aspects, including the initial diagnosis, neoadjuvant regimens, outcomes of surgical intervention, and overall survival at 2 years and 5 years following treatment. A total of 35 patients had neoadjuvant oncological treatment (mostly chemoradiation therapy) prior to surgery, out of which 28 patients were diagnosed with stage IIIA NSCLC. In post-operative assessment of pathological staging, downstaging was reported in 19 patients, of which 25% of cases were defined as a complete pathological response. The 2-year overall survival rate was 65% and the 5-year overall survival rate was 62%. The main pattern of disease recurrence was distant metastasis.

Impact assessment of critical success factors (CSFs) in public construction projects of Saudi Arabia

PurposeThere is a limited number of research work on critical success factors (CSFs) in public construction projects in Saudi Arabia. In response to this knowledge gap, the objective of this paper is to assess the impact of CSFs on the government construction projects in Saudi Arabia. The success factors are investigated from a broader consideration of failure criteria, from consideration of most effectiveness in successful project completion and also from consideration of the impact of implementing control processes for successful project completion.Design/methodology/approachThis study has analysed the impact of success factors on construction projects in Saudi Arabia using a descriptive methodology. An exhaustive literature survey is undertaken to identify the success and failure factors related to government construction projects in Saudi Arabia. The survey data are sorted out and analysed by cost, schedule, technical, context and finance dimensions of the projects based on project types, engineering complexity, size, modality, jurisdictional control and funding approach. To evaluate the influence of success factors implementation, qualitative data were collected in a survey via a web-based questionnaire that was sent to officials working and occupying a responsible position in national project guidelines organizations and in government construction organizations in Saudi Arabia. In all, 28 CSFs were identified, ranked and evaluated for their impact on project success. The four identified factors belong to process categories of construction projects, nine factors belong to management of construction projects and 15 success factors are identified for impact assessment of implementation in construction projects.FindingsThe study's findings have identified and ranked the top five CSFs that significantly influence project outcomes, including meeting time targets, adhering to financial budgets, delivering desired outcomes for all stakeholders, effectively managing risks and assembling the appropriate team while optimizing resource allocation. Additionally, the research indicates that hindrances to projects primarily stem from execution, economic, human and political factors. The study advocates for strict controls over incomplete engineering designs and advises against contractors independently handling design work to ensure project success. Additionally, addressing contractors' qualifications and financial matters is crucial for project success. By highlighting these CSFs and challenges, the research provides actionable insights to enhance project management practices in the construction industry.Research limitations/implicationsThis study is limited to the infrastructure projects constructed by governmental bodies with the participation of officials from government organizations. Further study, including private projects and officials working on private projects, may be needed to generalized the research outcome.Originality/valueNumerous studies have investigated CSFs in construction projects, but few have examined their relevance to Saudi Arabian government projects. This study aims to fill this gap by identifying key CSFs specific to Saudi Arabian public sector construction projects and assessing their impact on project success. It advocates for stringent controls in the Saudi Arabian construction sector, emphasizing the importance of preventing incomplete or altered engineering designs by contractors to increase the success rate of public sector projects. This research offers practical insights to stakeholders, advancing project management practices in Saudi Arabia's construction sector for improved outcomes and resource utilization.