Twin Analyses Research Articles

Construction error control method of large-span spatial structures based on digital twin

In the process of construction of large-span spatial structures, there are many control elements, which need to carry on the dual control of internal force and shape. The traditional control method cannot measure the construction deviation completely and accurately, and there is a lag in information feedback. In this paper, spatio-temporal information is integrated into digital twin and a construction error control method is proposed for large-span spatial structures. By analyzing the fusion mechanism of spatio-temporal information and digital twin, a closed-loop control system for structural errors before, during and after construction is formed. Driven by the control architecture, the method of structure simulation analysis and real-time monitoring during construction is proposed, and the functional relationship between cable force and cable length is established. Based on point cloud data, construction error optimization detection method is proposed for structure formation state. The nonlinear relation between elevation change rate and cable force deviation is formed and the control measures of formation state error are obtained. The experimental model of cable truss structure is taken as an example to apply and verify the theoretical method. The construction error control twin platform is formed in the experiment. Driven by the platform, the twinning analysis and real-time monitoring of the construction process are carried out to control the error of the structure formation. The results show that this method integrates spatio-temporal information into digital twin to realize data integration processing. The optimized error detection method can save 30% time cost and effectively control the construction error within 3%. The integration of spatio-temporal information and digital twin provides theoretical and algorithm support for the intelligent management and control of large-span spatial structure construction.

Investigating Trivariate Associations Between Risky Sexual Behavior, Internalizing Problems, and Externalizing Problems: A Twin Study.

Risky sexual behavior (RSB) has been linked to externalizing problems, substance use, and, in a recent study by our lab, internalizing problems. The current study builds upon previous work investigating the relationship between RSB and internalizing problems (INT) by controlling for externalizing problems (EXT) to account for the correlation between INT and EXT. We used a twin sample from Colorado (N = 2,544) to investigate phenotypic and genetic relationships between the three latent constructs, as well as potential sex differences in those relationships. We hypothesized that the relationship between RSB and INT would be stronger for females than for males, whereas the relationship between RSB and EXT would be stronger for males than for females. We used phenotypic confirmatory factor analysis and multivariate twin analyses to address research questions. Our results show significant phenotypic relationships among RSB, INT, and EXT and provide modest evidence in males for a significant association between RSB and INT that persists when controlling for EXT, a finding which we interpret with caution. Our sex differences hypothesis was not fully supported, although the direction of effects was in the direction hypothesized for the association between RSB and INT. We discuss the complexity of RSB as a phenotype and the potential implications for public health.

Zygosity Effects on Human Voice: Fundamental Frequency Analysis of Brazilian Twins' Speech.

Voice production can be influenced by interindividual variations related to genetic, physiological, behavioral, and several environmental factors. Here we examined the effect of zygosity on speaking fundamental frequency (F0) statistical descriptors. Our aims were: (1) to determine whether the genetic similarity between monozygotic (MZ) and dizygotic (DZ) twins affects F0 characteristics, and (2) to quantify the contribution of genetic factors to these characteristics. The study involved 79 same-sex twin pairs of Brazilian Portuguese speakers, comprising 65 MZ and 14 DZ twins, aged 18 to 66 years (31.7 ± 11.6 years), with 21 male and 58 female pairs. Participants were recorded while uttering a greeting phrase and the Brazilian Portuguese version of the 'Happy Birthday to You' song. Speech segments were analyzed using Praat free software, and F0 measures were automatically extracted in both Hertz and semitone scales. Statistical descriptors, including centrality, dispersion, and extreme values of F0 were examined, and the ACE model (i.e., total genetic effects, A; shared environmental influences, C; and nonshared environmental influences, E) was employed to estimate the additive effect;ts of monozygosity. As anticipated, we observed a zygosity effect on several F0 parameters, with more similarity between MZ twins compared to DZ twins. We discuss the genetic influences on F0 parameters and the absence of a monozygosity effect in two of them. Additionally, we briefly address potential biases associated with the selected measurement scale for statistical modeling. Finally, we explore the influence of genetic factors on F0 patterns, as well as environmental, life history and linguistic factors, particularly concerning F0 variation in speech.

Rotational deformation twins in a HfNbTaTiZr refractory high entropy alloy

Results of the analysis of deformation twins formed in a HfNbTaTiZr refractory high entropy alloy during compression deformation at 20 °C – 600 °C are reported. All studied twins were formed by rotation of the matrix crystal lattice around a 〈110〉 pole and have the common reciprocal twinning plane K2 = {001} and reciprocal twinning direction η2 = <11¯0>. At the same time, the twinning plane K1 and direction η1 depend on the degree of rotation of K2 and η2 around the common 〈110〉 pole. The following rotational twinning modes have been identified in HfNbTaTiZr: {11¯4}<22¯1¯> (38.94° rotation), {11¯5}<55¯2¯> (31.58°), {11¯6}<33¯1¯> (26.54°), {11¯7}<77¯2¯> (22.84°), and {11¯8}<44¯1¯> (20.04°). A rotational mechanism of twinning, with the rotation axis 〈011〉 or 〈001〉, is proposed as an alternative to the commonly accepted shear mechanism.

Depressive symptoms, cognitive functions and daily activities: An extended network analysis in monozygotic and dizygotic twins

BackgroundThe network theory posits that depression emerges as the result of individual symptoms triggering each other. Risk factors for depression can impact these between-symptoms interactions through extended networks. The study aimed to model the extended network of depressive symptoms and known depression risk factors – objective cognitive function, intellectual, physical, and social daily activities, and then, compare the observed networks between monozygotic (MZ) and dizygotic (DZ) co-twins. MethodsTwin pairs, 722 MZ and 2200 DZ, aged 40–79, were selected from the Dansh Twin Registry for having complete measures of depressive symptoms (e.g., sadness), cognitive functions (e.g., verbal memory), physical (e.g., brisk walk), intellectual (e.g., reading newspapers) and social activities (e.g., phone calls). Gaussian graphical models were used to estimate and compare the networks first between co-twins and then, between MZ to DZ twin pairs separately. ResultsSpecific intellectual, physical and social activities were central in the extended networks of depressive symptoms and, with the exception of processing speed, more central than cognition. The extended networks' structure was more homogeneous between MZ co-twins relative to DZ co-twins. Cognitive nodes were more central in MZ than DZ co-twins. LimitationsCross-sectional design, participants were middle-aged or older, mostly affective (non-somatic) depressive symptoms. ConclusionsIn depression networks, core connecting elements were intellectual, physical and social activities. The interaction between cognition and daily activities seems critical for triggering depressive symptoms. Thus, clinical interventions aimed at preventing depression and associated cognitive deficits should focus on maintenance and/or engagement in stimulating daily activities.

Sleep inertia drives the association of evening chronotype with psychiatric disorders: epidemiological and genetic evidence.

Evening chronotypes (a.k.a. night-owls) are held to be at greater risk for psychiatric disorders. This is postulated to be due to delayed circadian timing increasing the likelihood of circadian misalignment in an early-oriented society. Circadian misalignment is known to heighten sleep inertia, the difficulty transitioning from sleep to wake characterized by low arousal and cognitive impairment, and evening chronotypes experience greater sleep inertia. Therefore, difficulty awakening may explain the relationship between evening chronotype and psychiatric disorders by acting as a biomarker of circadian misalignment. In analyzing the longitudinal incidence of psychiatric disorders in the UK Biobank (n = 496,820), we found that evening chronotype predicted increased incidence of major depressive disorder, schizophrenia, generalized anxiety disorder and bipolar disorder. Crucially, this effect was dependent on sleep inertia, which was a much stronger predictor of these disorders, such that evening types without sleep inertia were at no higher risk as compared to morning types. Longitudinal analyses of suicide and depressed mood (CES-D score) in the Older Finnish Twin Cohort (n = 23,854) replicated this pattern of results. Twin and genome-wide association analyses of difficulty awakening identified the trait to be heritable (Twin H2 = 0.40; SNP h2 = 0.08), enriched for circadian rhythms genes and have substantial shared genetic architecture with chronotype. Marginal and conditional Mendelian randomization analyses mirrored the epidemiological results, such that the causal effect of evening chronotype on psychiatric disorders was driven by shared genetic architecture with difficulty awakening. In contrast, difficult awakening was strongly causally associated with psychiatric disorders independently of chronotype. Psychiatric disorders were only weakly reverse causally linked to difficult awakening. Collectively, these results challenge the notion that evening chronotype is a risk factor for psychiatric disorders per se, suggesting instead that evening types are at greater risk for psychiatric disorders due to circadian misalignment, for which sleep inertia may be acting as a biomarker.

Effect of the strain rate on the deformation mechanisms of TWIP-type steel

This paper describes the influence of the strain rate on the microstructure of X55MnAl25-5 steel from the group of high-manganese steels exhibiting the twinning-induced plasticity effect. The tests were carried out at a wide range of strain rates, starting with static tensile tests where the appropriate strain rates were 0.005 s−1, and ending with tests using a flywheel machine at strain rates of 1830 s−1 and 4650 s−1. The increase in the applied strain rate on the example of the tested steel results in hardening. Evolutionary changes leading to the predominance of dislocation slipping over the twinning are observed in the microstructure under static deformation conditions. The increase in the intensity of twinning with the simultaneous decrease in the mobility of dislocations progresses as the strain rate increases. The microstructure evolution was characterized using light optical microscopy and scanning electron microscopy, including electron backscatter diffraction. The qualitative analysis of the deformation twins was performed. For the lowest strain rate, 5·10−4 s−1, deformation twins appear in a single twinning system, while increasing the strain rate leads to the activation of multiple twinning systems. Proceeding to the range of dynamic tests reveals an increase in the participation of the twinning mechanism in the deformation of the examined steel. With an increasing strain rate, the effect of texture on the twinning process activity decreases. Based on the obtained results, a diagram was elaborated that presents the microstructural changes which take place in X55MnAl25-5 steel after deformation under static and dynamic tensile conditions in graphical form.

Multi-omics association study of DNA methylation and gene expression levels and diagnoses of cardiovascular diseases in Danish Twins

BackgroundCardiovascular diseases (CVDs) are major causes of mortality and morbidity worldwide; yet the understanding of their molecular basis is incomplete. Multi-omics studies have significant potential to uncover these mechanisms, but such studies are challenged by genetic and environmental confounding—a problem that can be effectively reduced by investigating intrapair differences in twins. Here, we linked data on all diagnoses of the circulatory system from the nationwide Danish Patient Registry (spanning 1977–2022) to a study population of 835 twins holding genome-wide DNA methylation and gene expression data. CVD diagnoses were divided into prevalent or incident cases (i.e., occurring before or after blood sample collection (2007–2011)). The diagnoses were classified into four groups: cerebrovascular diseases, coronary artery disease (CAD), arterial and other cardiovascular diseases (AOCDs), and diseases of the veins and lymphatic system. Statistical analyses were performed by linear (prevalent cases) or cox (incident cases) regression analyses at both the individual-level and twin pair-level. Significant genes (p < 0.05) in both types of biological data and at both levels were inspected by bioinformatic analyses, including gene set enrichment analysis and interaction network analysis.ResultsIn general, more genes were found for prevalent than for incident cases, and bioinformatic analyses primarily found pathways of the immune system, signal transduction and diseases for prevalent cases, and pathways of cell–cell communication, metabolisms of proteins and RNA, gene expression, and chromatin organization groups for incident cases. This potentially reflects biology related to response to CVD (prevalent cases) and mechanisms related to regulation and development of disease (incident cases). Of specific genes, Myosin 1E was found to be central for CAD, and DEAD-Box Helicase 5 for AOCD. These genes were observed in both the prevalent and the incident analyses, potentially reflecting that their DNA methylation and gene transcription levels change both because of disease (prevalent cases) and prior disease (incident cases).ConclusionWe present novel biomarkers for CVD by performing multi-omics analysis in twins, hereby lowering the confounding due to shared genetics and early life environment—a study design that is surprisingly rare in the field of CVD, and where additional studies are highly needed.

Genetic associations between non-cognitive skills and academic achievement over development

Non-cognitive skills, such as motivation and self-regulation, are partly heritable and predict academic achievement beyond cognitive skills. However, how the relationship between non-cognitive skills and academic achievement changes over development is unclear. The current study examined how cognitive and non-cognitive skills are associated with academic achievement from ages 7 to 16 years in a sample of over 10,000 children from England and Wales. The results showed that the association between non-cognitive skills and academic achievement increased across development. Twin and polygenic scores analyses found that the links between non-cognitive genetics and academic achievement became stronger over the school years. The results from within-family analyses indicated that non-cognitive genetic effects on academic achievement could not simply be attributed to confounding by environmental differences between nuclear families, consistent with a possible role for evocative/active gene–environment correlations. By studying genetic associations through a developmental lens, we provide further insights into the role of non-cognitive skills in academic development.

Development of temperament types from infancy to adolescence: Genetic and environmental influences with an economically and racially/ethnically diverse sample.

Kagan theorized biologically based temperament types that are present in infancy, stable across development, and essential for understanding individual differences. Despite evidence, temperament research remains focused on a few prominent dimensions of temperament, without adequately addressing covariance among dimensions and temperament types. Using longitudinal twin data, we took a person-centered statistical approach to identify temperament types and examined continuity and change across five developmental periods (Ninfancy = 602; Ntoddlerhood = 522; Nearly childhood = 390; Nlate childhood = 718; Nearly adolescence = 700). We then examined the genetic and environmental etiology of temperament types. Twins were boys and girls (51-53% female), primarily Hispanic/Latinx (23-30%) and non-Hispanic/Latinx White (56-63%), and from socioeconomically diverse families (28-38% near-or-below the poverty line). Using latent profile analysis, we identified three temperament types at each age characterized by negative reactivity and dysregulation, positive reactivity and strong self-regulation, and moderate reactivity and regulation. Latent transition analyses revealed considerable continuity in membership type for "negative dysregulated" beginning in infancy, log odds = 1.58 (SE = .65) to 3.16 (SE = .77), p < .01, of remaining relative to transitioning to "typical expressive", and "positive well-regulated" beginning in early childhood, log odds = 1.41 (SE = .56) to 2.25 (SE = .47), p < .05. Twin analyses revealed moderate heritability and a consistent role of the shared environment on positive well-regulated, with negative dysregulated and typical expressive also moderately heritable with the shared environment being important at some ages. Findings support the presence of theorized biologically based temperament types that develop rapidly in infancy and toddlerhood and provide a foundation for the study of individual differences and risk and resilience processes across the lifespan. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Age at separation, residential mobility, and depressive symptoms among twins in late adolescence and young adulthood: a FinnTwin12 cohort study

BackgroundSeparating with close siblings and leaving the parental home at an early age represents a major life event for an adolescent (reflected by age at separation in a twin pair) and may predispose them to poor mental health. This study aims to examine the association of age at separation and residential mobility on depressive symptoms in late adolescence and young adulthood and to explore possible underlying genetic effects.MethodsResidential mobility consisted of the number and total distance of moves before age 17. Based on 3071 twins from the FinnTwin12 cohort, we used linear regression to assess the association of age at separation and residential mobility with General Behavior Inventory (GBI) scores at age 17 and in young adulthood. A higher GBI score indicated more depressive symptoms occurred. Then, the mixed model for repeated measures (MMRM) was used to visualize the scores’ trajectory and test the associations, controlling for "baseline" state. Twin analyses with a bivariate cross-lagged path model were performed between the difference in GBI scores, between cotwins, and separation status for the potential genetic influence.ResultsCompared to twins separated before age 17, twins who separated later had significantly lower GBI scores at age 17 and in young adulthood. In MMRM, separation at a later age and a higher number of moves were associated with a higher GBI score in young adulthood. A small genetic effect was detected wherein GBI within-pair differences at age 17 were associated with separation status before age 22 (coefficient: 0.01).ConclusionThe study provides valid evidence about the influence of siblings and family on depressive symptoms in later adolescence and young adulthood while finding some evidence for a reverse direction effect. This suggests more caution in the interpretation of results. A strong association between residential mobility and depressive symptoms was affirmed, although further detailed research is needed.

Multi-polygenic score prediction of mathematics, reading, and language abilities independent of general cognitive ability.

Specific cognitive abilities (SCA) correlate genetically about 0.50, which underpins general cognitive ability (g), but it also means that there is considerable genetic specificity. If g is not controlled, then genomic prediction of specific cognitive abilities is not truly specific because they are all perfused with g. Here, we investigated the heritability of mathematics, reading, and language ability independent of g (SCA.g) using twins and DNA, and the extent to which multiple genome-wide polygenic scores (multi-PGS) can jointly predict these SCA.g as compared to SCA uncorrected for g. We created SCA and SCA.g composites from a battery of 14 cognitive tests administered at age 12 to 5,000 twin pairs in the Twins Early Development Study (TEDS). Univariate twin analyses yielded an average heritability estimate of 40% for SCA.g, compared to 53% for uncorrected SCA. Using genome-wide SNP genotypes, average SNP-based heritabilities were 26% for SCA.g and 35% for SCA. We then created multi-PGS from at least 50 PGS to predict each SCA and SCA.g using elastic net penalised regression models. Multi-PGS predicted 4.4% of the variance of SCA.g on average, compared to 11.1% for SCA uncorrected for g. The twin, SNP and PGS heritability estimates for SCA.g provide further evidence that the heritabilities of SCA are not merely a reflection of g. Although the relative reduction in heritability from SCA to SCA.g was greater for PGS heritability than for twin or SNP heritability, this decrease is likely due to the paucity of PGS for SCA. We hope that these results encourage researchers to conduct genome-wide association studies of SCA, and especially SCA.g, that can be used to predict PGS profiles of SCA strengths and weaknesses independent of g.

AI-Driven BIM Integration for Optimizing Healthcare Facility Design

Efficient healthcare facility design is crucial for providing high-quality healthcare services. This study introduces an innovative approach that integrates artificial intelligence (AI) algorithms, specifically particle swarm optimization (PSO), with building information modeling (BIM) and digital twin technologies to enhance facility layout optimization. The methodology seamlessly integrates AI-driven layout optimization with the robust visualization, analysis, and real-time capabilities of BIM and digital twins. Through the convergence of AI algorithms, BIM, and digital twins, this framework empowers stakeholders to establish a virtual environment for the streamlined exploration and evaluation of diverse design options, significantly reducing the time and manual effort required for layout design. The PSO algorithm generates optimized 2D layouts, which are seamlessly transformed into 3D BIM models through visual programming in Dynamo. This transition enables stakeholders to visualize, analyze, and monitor designs comprehensively, facilitating well-informed decision-making and collaborative discussions. The study presents a comprehensive methodology that underscores the potential of AI, BIM, and digital twin integration, offering a path toward more efficient and effective facility design.

Developmental trajectories of child and adolescent emotional problems: associations with early adult alcohol use behaviors.

Whether emotional problems during childhood and adolescence are longitudinally associated with adult alcohol use behaviors is unclear. This study examined associations between developmental trajectories of emotional problems and early adult alcohol use behaviors, while considering co-occurring conduct problems, developmental change/timing, sex differences, and potential confounds. Participants were from the Twins Early Development Study (analytic N = 19,908 individuals). Emotional and conduct problems were measured by parent reports at child ages 4, 7, and 9 years and via self-reports at ages 9, 11, and 16 years on the Strengths and Difficulties Questionnaire. Alcohol use behaviors (alcohol consumption and alcohol-related problems) were self-reported by the twins on the Alcohol Use Disorders Identification Test at age 22 years. Piecewise latent growth curve models described nonlinear developmental trajectories of emotional and conduct problems from ages 4 to 16. At age 22, alcohol use was regressed on emotional and conduct problems' intercepts and slopes from piecewise latent growth curve model and sex differences in regression coefficients were tested. Using twin modeling, Cholesky decompositions and direct path models were compared to test whether significant phenotypic associations were best explained by direct phenotypic influences or correlated genetic and environmental influences. Emotional problems had different associations with alcohol-related problems versus alcohol consumption. After accounting for direct influences from conduct problems, emotional problems were not associated with alcohol-related problems, while emotional problems at age 9 were negatively associated with alcohol consumption in males. Overall, findings did not support emotional problems as prospective risk factors for severe alcohol use above and beyond risks associated with conduct problems. Sex- and age-specific links between emotional problems and alcohol consumption in early adulthood may be worthy of further exploration, particularly as twin analyses improved our confidence that such links may be underpinned by causal mechanisms.

Bibliometric Analysis of Digital Twins (DTS) Application for Improving Sustainable Logistics in Supply Chains

Bibliometric Analysis of Digital Twins (DTS) Application for Improving Sustainable Logistics in Supply Chains

Comprehensive analysis of digital twins in smart cities: a 4200-paper bibliometric study

This survey paper comprehensively reviews Digital Twin (DT) technology, a virtual representation of a physical object or system, pivotal in Smart Cities for enhanced urban management. It explores DT's integration with Machine Learning for predictive analysis, IoT for real-time data, and its significant role in Smart City development. Addressing the gap in existing literature, this survey analyzes over 4,220 articles from the Web of Science, focusing on unique aspects like datasets, platforms, and performance metrics. Unlike other studies in the field, this research paper distinguishes itself through its comprehensive and bibliometric approach, analyzing over 4,220 articles and focusing on unique aspects like datasets, platforms, and performance metrics. This approach offers an unparalleled depth of analysis, enhancing the understanding of Digital Twin technology in Smart City development and setting a new benchmark in scholarly research in this domain. The study systematically identifies emerging trends and thematic topics, utilizing tools like VOSviewer for data visualization. Key findings include publication trends, prolific authors, and thematic clusters in research. The paper highlights the importance of DT in various urban applications, discusses challenges and limitations, and presents case studies showcasing successful implementations. Distinguishing from prior studies, it offers detailed insights into emerging trends, future research directions, and the evolving role of policy and governance in DT development, thereby making a substantial contribution to the field.

Application of the polyhedral template matching method for characterization of 2D atomic resolution electron microscopy images

High-throughput image segmentation of atomic resolution electron microscopy data poses an ongoing challenge for materials characterization. In this paper, we investigate the application of the polyhedral template matching (PTM) method, a technique widely employed for visualizing three-dimensional (3D) atomistic simulations, to the analysis of two-dimensional (2D) atomic resolution electron microscopy images. This technique is complementary with other atomic resolution data reduction techniques, such as the centrosymmetry parameter, that use the measured atomic peak positions as the starting input. Furthermore, since the template matching process also gives a measure of the local rotation, the method can be used to segment images based on local orientation. We begin by presenting a 2D implementation of the PTM method, suitable for atomic resolution images. We then demonstrate the technique's application to atomic resolution scanning transmission electron microscopy images from close-packed metals, providing examples of the analysis of twins and other grain boundaries in FCC gold and martensite phases in 304 L austenitic stainless steel. Finally, we discuss factors, such as positional errors in the image peak locations, that can affect the accuracy and sensitivity of the structural determinations.

Brain reserve in midlife is associated with executive function changes across 12 years

We examined how brain reserve in midlife, measured by brain-predicted age difference scores (Brain-PADs), predicted executive function concurrently and longitudinally into early old age, and whether these associations were moderated by young adult cognitive reserve or APOE genotype. 508 men in the Vietnam Era Twin Study of Aging (VETSA) completed neuroimaging assessments at mean age 56 and six executive function tasks at mean ages 56, 62, and 68 years. Results indicated that greater brain reserve at age 56 was associated with better concurrent executive function (r=.10, p=.040) and less decline in executive function over 12 years (r=.34, p=.001). These associations were not moderated by cognitive reserve or APOE genotype. Twin analysis suggested associations with executive function slopes were driven by genetic influences. Our findings suggest that greater brain reserve allowed for better cognitive maintenance from middle- to old age, driven by a genetic association. The results are consistent with differential preservation of executive function based on brain reserve that is independent of young adult cognitive reserve or APOE genotype.

Digital Twin and Simulation Analyses for Process Optimization of an Automated Guided Vehicle System

Development in industrial companies aims to digitize processes, ensure traceability and advance automation. Systems with automated guided vehicles (AGVs) can help meet these objectives. A core element of these systems is the higher-level system controller. When an AGV system is operated, some dynamic aspects appear. It is then to identify, that the previous specified rules for scheduling and routing of vehicles are not always proper and practical, which may result in waiting time of AGVs. That means the static performance requirements and the specifications based on them often lead to suboptimal results. A methodical problem-solving approach is to develop a digital twin as a reflection of reality and to carry out strategy analyses using simulation. For this purpose, a digital twin of the concerned AGV system with five vehicles and its technological environment is created using software of plant simulation. Various simulation scenarios are developed to simulate material flows by using different routing and scheduling rules and strategies. Drawing from the insights gained through the digital twin and simulation analyses, this study identifies novel scheduling and routing rules for the AGV system. These rules improve the overall efficiency and effectiveness of the system operations by easing traffic congestion, reducing transit time, and minimizing production downtime.

Analysis of Digital Twins in the Construction Industry: Practical Applications, Purpose, and Parallel with other Industries

Digital twins (DTs) have become a widely discussed subject, believed to have the potential to solve various problems across different industries, including Engineering &amp; Construction (E&amp;C). However, there is still significant misconception concerning the definition of DTs and their purpose within E&amp;C. This study dives deep into identifying DT applications within E&amp;C and the other prominent industries, i.e., Aerospace &amp; Aviation, Manufacturing, Energy &amp; Utilities, Automotive, Healthcare, Smart Cities, Oil &amp; Gas, and Retail. The main challenges to the evolution of DT practical applications are also analyzed. A combination of a literature review, multi-case study analysis, and comparative analysis compose the deployed methodology. Standardization and a maturity level classification are proposed to drive progress of the adoption of DTs. The distinct aspects of the different industries and their assets are evaluated to the conclusion that DTs are better employed for maintenance of structures within E&amp;C. DTs have become a well-worn topic, but the abundance of complex theoretical frameworks is met with simple or inexistent practical applications. Therefore, the novelty of this study lays in its comprehensive analysis of DT applications and real-world implementations—a departure from the often-theoretical discussions surrounding DTs.