Routine Design Research Articles

How do Ritz Vectors React to the Imposed Load?

All real structures behave dynamically when loaded or displaced. Additional inertial forces are equal to the force in acceleration using Newton's second law. If the forces or the change of places are applied very slowly, the inertial forces can be ignored and a static analysis can be done. Therefore, it can be said that dynamic analysis is a simple extension of static analysis. In addition, all potential real structures have unlimited degrees of freedom. Therefore, the most critical part of structural analysis is creating a model with a limited number of degrees of freedom that has several almost massless members and several nodes, which can estimate the behavior of the structure appropriately. The mass of the structure can be concentrated in the nodes. Also, for a linear elastic system, the stiffness characteristics of the members can be estimated very accurately - according to the experimental data - although the estimation of dynamic loading, energy loss, and boundary conditions can be very difficult. Therefore, the nonlinear dynamic analysis method is usually used in theoretical studies and is not used in routine designs. So, it is a worthwhile task to propose a simple and computer method for seismic estimation of structures. For this purpose, POA has been introduced. In many cases, we can get more valuable information from POA than nonlinear dynamic analysis, this method is simple and economical and has attracted more attention nowadays.

Concordance of patient- and clinician-reported outcomes of acute radiation dermatitis in breast cancer.

The study evaluated the concordance between patient-reported outcomes (PRO) and clinician-reported outcomes (CRO) of acute radiation dermatitis (RD) symptoms following adjuvant radiotherapy for early-stage and locally advanced breast cancer. This is a secondary analysis of a multi-center randomized phase 3 trial (376 patients). Ordinal logistic regression analysis was used to compare the Skin Symptom Assessment (SSA) independently reported by both patients and clinicians. Concordance between patient- and clinician-reported SSAs for RD symptoms was measured by percent concordance, concordance index (C-statistic), and Cohen's Kappa. Analyses were performed across all patients in the original modified intention-to-treat analysis and those with only grade 2-3 (CTCAE) RD. PROs were significantly more severe than CROs across all RD symptoms (Odds Ratio [OR] > 1; p < 0.0001). Pigmentation (OR 5.4), blistering/peeling (OR 4.0), and pain/soreness (OR 3.9) were the most differentially reported symptoms. Poor-to-low concordance was noted between patient- and clinician-reported SSAs for all RD symptoms for the entire cohort (percent concordance < 50%, C-statistic 0.52-0.63, Cohen's Kappa 13.9-23.4%) and those with grade 2-3 RD (percent concordance < 50%, C-statistic 0.56-0.66, Cohen's Kappa 2.0-24.5%). Similarly, poor-to-low concordance was noted in both Mepitel film and standard-of-care arms. PROs and CROs have poor concordance in breast RD, and patients report worse outcomes than clinicians, regardless of RD severity or prophylaxis. PROs must be further integrated into routine clinical practice and clinical trial design to reduce the risk of underreporting symptoms.

Machine learning-based surrogate resilience modeling for preliminary seismic design

Early decisions made during the preliminary seismic design, particularly regarding the stiffness and strength of the selected lateral force-resisting system, have a significant impact on seismic resilience. However, the effects of these crucial decisions on resilience are not explicitly assessed until the end of the routine code-based design. The indirect design approach can bring about substantial design iterations that involve computationally expensive resilience assessment. For the support of direct resilience-informed design, this paper employs machine learning techniques to develop a surrogate model that maps site and building features to resilience indices. The surrogate model aids design practitioners in selecting satisfying design combinations of stiffness and strength in the preliminary seismic design. It provides real-time feedback on the resulting resilience, drastically reducing the time and effort required for iterative design revisions. To demonstrate the effectiveness of the proposed approach, a data set of 10,000 steel moment-resisting frames (SMRFs) with wide-ranging design combinations is created; additionally, six regression algorithms, including linear regression, support vector regression, multi-layer perceptron, k-nearest neighbors, decision tree, and extreme gradient boosting (XGBoost), are used to establish the surrogate model. Among the six algorithms, XGBoost performed the best in terms of the lowest RMSE (0.031) and the highest R2 (0.97) for the test set. Identified by the SHapley Additive exPlanations (SHAP) approach, the seismic hazard-related design basic acceleration and the stiffness-related building period coefficient have the most significant impact on the prediction of XGBoost. This enables a physical and quantitative understanding of the surrogate estimates.

Finite-element-based cross-section analysis method for functionally graded sandwich members with arbitrary shapes and gradients

Recent advancements in manufacturing technologies have facilitated the efficient and cost-effective production of functionally graded (FG) sandwich members, offering exceptional structural performances. However, designing these members is challenging due to the difficulties in accurately determining their cross-sectional properties, especially within routine designs that rely on beam-column elements. To this end, this paper introduces a robust finite-element-based cross-section analysis method for FG sandwich sections considering arbitrary shapes and material gradients. A novel nonhomogeneous plane triangle (NPT) element is formulated to enhance the computational efficiency of the developed cross-section analysis approach. A new structural analysis software with a graphic user interface, namely MSASect2, is developed based on the proposed cross-section analysis approach for its convenient implementation in practice. Four examples are displayed to verify the correctness of the present study and MSASect2, indicating their potential to promote the broader application of FG sandwich sections.

Analytical solution of conductor tensile force in asymmetrical spans used in overhead power lines and substations with influence of tension insulators

Introduction. Designing electrical substations involves analyzing the horizontal tensile force in flexible tension conductors under varying temperatures. These temperature changes affect the conductor’s length and forces. Problem. Existing methods for calculating horizontal tensile force in conductors often focus on symmetric spans or require complex finite element modeling (FEM), which is impractical for routine substation design. Asymmetric spans with tension insulators present a more complex challenge that current solutions do not adequately address. Purpose. Universal analytical solution and algorithm for calculating the horizontal tensile forces in conductors in asymmetric spans with tension insulators used in power substations or short overhead power line spans. The solution is designed to be easily implementable in software without requiring complex tools or extensive FEM. Methodology. The methodology involves deriving an analytical solution based on the catenary curve formed by the conductor between attachment points at different heights. The analysis includes calculating the conductor’s length for a given tensile force and using a state change equation to determine forces under new temperature conditions. Validation is performed using FEM calculations. Results. The proposed solution was validated against FEM models with varying height differences (5 m and 15 m) and conductor temperatures (–30 °C, –5 °C, +80 °C). The results showed a minimal error (less than 0.15 %) between the analytical solution and FEM results, demonstrating high accuracy. Originality. This paper presents a novel analytical solution to the problem of calculating tensile forces in asymmetric spans with tension insulators. Unlike existing methods, our solution is straightforward and easily implementable in any programming language. Practical value. The solution is practical for routine design tasks in electrical substations or short overhead power lines. Especially in power substations, accurate tensile forces are needed not only for mechanical design and sag calculations but also for calculating the dynamic effects of short-circuit currents. References 23, tables 4, figures 3.

Guide RNA structure design enables combinatorial CRISPRa programs for biosynthetic profiling

Engineering metabolism to efficiently produce chemicals from multi-step pathways requires optimizing multi-gene expression programs to achieve enzyme balance. CRISPR-Cas transcriptional control systems are emerging as important tools for programming multi-gene expression, but poor predictability of guide RNA folding can disrupt expression control. Here, we correlate efficacy of modified guide RNAs (scRNAs) for CRISPR activation (CRISPRa) in E. coli with a computational kinetic parameter describing scRNA folding rate into the active structure (rS = 0.8). This parameter also enables forward design of scRNAs, allowing us to design a system of three synthetic CRISPRa promoters that can orthogonally activate (>35-fold) expression of chosen outputs. Through combinatorial activation tuning, we profile a three-dimensional design space expressing two different biosynthetic pathways, demonstrating variable production of pteridine and human milk oligosaccharide products. This RNA design approach aids combinatorial optimization of metabolic pathways and may accelerate routine design of effective multi-gene regulation programs in bacterial hosts.

#614 Identifying distinct patient phenotypes in patients with chronic kidney disease

Abstract Background and Aims Patients with chronic kidney disease (CKD) are heterogeneous in terms of age, causes of CKD, and comorbidities. Although individual risk factors greatly influence patients’ risk of clinical outcomes, this heterogeneity is rarely used to guide clinical decision-making. In this study we aimed to derive phenotypes in patients with CKD based on characteristics commonly available in routine clinical practice and evaluated whether these phenotypes were associated with clinical outcomes. Method Patients from the Utrecht Patient Oriented Database (UPOD) who were 18 years or older with CKD (defined as an eGFR &amp;lt;60 ml/min/1.73 m2 or an UACR &amp;gt; 3 mg/mmol present for &amp;gt;3 months) and visited one of the cardiovascular outpatient clinics of the University Medical Center Utrecht between 2012 and 2019 were included. Patient phenotypes were derived with latent class analyses based on age, sex, CKD stage, cause of kidney disease, and (cardiovascular) comorbidities. The incidence rate/100 person years (IR/100PY) for all-cause mortality and kidney failure (defined as initiation of kidney replacement therapy or a sustained eGFR &amp;lt;15) and 95% confidence interval (95% CI) was calculated for each phenotype. Results Overall 9005 patients were included (mean age 65 ± 14 years, 42% women, mean estimated glomerular filtration rate (eGFR) 49 ± 17 ml/min/1.73 m2). The median follow-up was 3.8 years [interquartile range 1.8–6.4]. Latent class analysis identified 7 phenotypes with the following characteristics: phenotype 1 were young patients with primary kidney disease (10%); phenotype 2 were patients with diabetes and a preserved eGFR (9%); phenotype 3 were patients with low comorbidity and inflammation (28%); phenotype 4 were older patients with a history of cardiovascular disease (27%); phenotype 5 were older patients with a history of cardiovascular disease and severe CKD (16%); phenotype 6 were younger patients with a kidney transplant and low comorbidity (6%); and phenotype 7 were older patients with a kidney transplant and cardiovascular disease (6%). The risk of all-cause mortality and kidney failure differed significantly between the identified phenotypes. The phenotypes of younger kidney transplant recipients, younger patients with primary kidney disease, and diabetes with preserved eGFR had the lowest risk for all-cause mortality (for all, IR/100 PY &amp;lt;5) (Fig. 1). The phenotypes with an intermediate incidence rate for all-cause mortality were the low comorbidity and inflammation phenotype (IR/100PY 7.4, 95% CI 6.9–8.0), the phenotype of older patients with cardiovascular disease (IR/100PY 7.2, 95% CI 6.7–7.8), and the phenotype of older patients with a kidney transplant and cardiovascular disease (IR/100PY 6.5, 95% CI 5.5–7.6). The phenotypes with highest incidence rate for all-cause mortality was the phenotype of older patients with cardiovascular disease and severe CKD (IR/100PY 12.5, 95% CI11.5–13.4). The phenotypes with the lowest risk for kidney failure were the diabetes phenotype, the low comorbidity and inflammation phenotype, and the phenotype of older patients with cardiovascular disease (all IR/100 PY &amp;lt;1). The phenotype of older patients with cardiovascular disease and severe CKD also had the highest risk to develop kidney failure (IR/100PY 5.8, 95% CI 5.1–6.6), followed by the phenotype of patients with primary kidney disease (IR/100PY 4.4, 95% CI 3.7 −5.5). Conclusion We identified 7 different phenotypes of patients with CKD including 2 phenotypes of patients with a kidney transplant with different clinical characteristics and prognosis. The differences in risk of all-cause mortality and kidney failure warrants a different monitoring and follow-up across the different phenotypes within the setting of CKD. Future studies should invest In evaluating the implementation of our identified phenotypes in routine clinical practice or clinical trial design with respect to differences in treatments.

A Critical Review of Methods for Backfill Soil Modulus in Design of Flexible Culverts

Flexible culverts made of corrugated steel or plastic are cost-effective and environmentally friendly alternatives to conventional small road and railway bridges. These structures interact with the backfill by deflecting when subjected to overburden loads, enabling them to utilize the surrounding soil by carrying loads in ring compression. In low soil cover situations, the relationship between bending and backfill soil (stiffness) modulus increasingly influences bearing capacity, and therefore must be considered in design. Backfill soil modulus is a direct result of the execution of the backfilling, and recognized as the most important design parameter because of local uncertainties during construction and material variability. This paper gives a review of some of the existing methods for determining backfill soil modulus. It covers development history, theoretical approximations, aspects of crushed rock materials and their quality, and ease of use in routine design. By applying the methods on different materials and comparing the end results with a compilation of large-scale compression tests and materials from various origins, the performance of the reviewed methods is evaluated. It is found that the reviewed methods have specific drawbacks depending on the actual stress condition and backfill material being applied. In addition, most methods are based on reference laboratory tests carried out on specific and sometimes high-quality materials, and therefore fail to reflect how the quality of rock materials influences the backfill modulus. These shortcomings are used to suggest a new outlook that should be considered in future research on backfill design.

Exploring the filtration performance and usage cost of commercial fiber air filters for capturing moxa smoke aerosols

Traditional moxibustion treatments plays a role in preventing and treating COVID-19 while aggravating indoor air pollution. Therefore, commercial fiber air filters (CFAF) are widely used to improve indoor air quality to reduce the risk of people being exposed to moxa smoke aerosols (MSA). Considering that there were few reports on the performance of CFAF for capturing MSA, we explored in detail the effects of face velocity and MSA particle size on the filtration performance of CFAF to fill this gap. Then, we analyzed the deposition characteristics of MSA on fibers in combination with SEM images. In addition, the long-term stability, cleaning performance and MSA holding capacity of the CFAF were further characterized by tests of continuous operation, clean air delivery rate (CADR) and MSA loading. The results indicated that the CFAF had the potential to efficiently capture MSA in indoor air at an acceptable annual usage cost (AUC). Specifically, the pristine CFAF had high classification counting efficiency (CCE) (99.1 %-100 %), medium pressure drop (150.3 Pa), and low quality factor (0.04 Pa−1) at the face velocity of 0.3 m·s−1. Note that increasing face velocity not only decreased CCE and quality factor but also significantly increased pressure drop. Furthermore, the CFAF maintained excellent CCE (99.5 %-100 %) after 24-h of continuous operation at high concentrations of MSA (100 mg·m−3), while the pressure drop increased to 203.7 Pa. Obviously, the deposited MSA severely clogged the inter-fiber pores, which explained the fact of the rapid increase in the pressure drop of the CFAF. Of course, the high CADR value (66.6 m3·h−1) also demonstrated that the CFAF had the ability to efficiently remove MSA from confined place. Moreover, a total of 216.3 g MSA can be captured by the CFAF when the final pressure drop reached 300 Pa, which meant that further increasing the MSA holding capacity would be the focus of future research by filter media manufacturers. Finally, through the established mathematical model, we successfully predicted the service life (86 days) and the total AUC (276 $·year−1) of using the CFAF to capture MSA. This work is expected to provide a useful reference for routine maintenance and design optimization of existing CFAF.

Estimating structural response to bidirectional seismic excitation using spectrum compatible motions: Performance of a pair of companion spectra

AbstractBidirectional analyses covering a range of incidence angles for several records are essential yet challenging for routine design. Recent studies have shown that the response to bidirectional shaking may be estimated per straightforward unidirectional analysis in the most preferred orientation in conjunction with the orthogonal combination rules, and this can also remove the need for various incidence angles. Further, it is well known that the mean response can be estimated with reduced dispersion using fewer spectrum‐compatible records. Combining the advantages of both, a pair of companion spectra independent of period and orientation has recently been developed. While the basis of the companion spectra is established therein from a sound mathematical perspective, the applicability of the proposed spectra to real structures may be revisited, especially to structures sensitive to bidirectional interaction, before recommending the companion spectra for practical design. To achieve this end, following a brief scrutiny of the companion spectra, the performance of the same is critically examined for idealized SDoF analogues and real structures such as bridge piers representative of SDoF systems and buildings with asymmetry using single storey and multistorey models (MDoF systems). The results show that the response of the real structures to bidirectional seismic loading can be reasonably estimated with reduced dispersion using fewer records compatible with the pair of the companion spectra. As such, the critical response parameters may be computed by actual bidirectional analyses or by combining responses to unidirectional analyses under fewer spectrum compatible records. Hence, the pair of companion spectra that can be used as “target” to independently match two components of a chosen record is useful for practical design.

Analysis of deformations of road embankments founded on displacement columns improving soft subsoil

Drilled displacement columns, constructed in the form of unreinforced or reinforced concrete elements, are currently a very commonly used method of improving soft subsoil, creating an alternative to more expensive pile foundations. A frequently used solution for improving soft soils of road or railway embankments is to design a regular pattern of columns of relatively small diameter. Columns along the perimeter of the improved area are reinforced with rigid steel profiles, while the internal ones are made as concrete elements. Column heads are usually covered with a load transfer platform (layer of compacted granular fill) which is additionally reinforced with geosynthetics. The application of soil improvement with displacement columns is not always successful. It is due to the errors and shortcomings occurring at the design stage, including simplifications in modelling, to construction faults, which may include insufficient experience of contractors and/or improper supervision. Referring to the real object that failed, the article provides the results of numerical parametric analyses taking into account the influence of the key design parameters such as: the stiffness of the load transfer layers, the amount and stiffness of the geosynthetic reinforcement as well as the column spacing. The article presents comparisons of numerical results obtained with the finite element analyses for various approaches to geometry modelling (axisymmetric, 2D and 3D). The simulations indicate that the use of the axisymmetric model of a single column in routine design may lead to the deformations exceeding the serviceability limit states.

Ground settlement prediction for open caisson shafts in sand using a neural network constrained by empiricism

Accurate prediction of soil settlements induced by open caisson construction in sand is essential for safe and reliable delivery of critical underground urban infrastructure. This paper presents a novel prescriptive design approach using a neural network (NN) constrained by empirical relationships, referred to as an ’empiricism-constrained neural network’. The proposed approach is benchmarked using a traditional closed-form empirical expression. Both methods are calibrated using experimental data from reduced-scale laboratory testing for the prediction of surface and subsurface settlement trough shape and magnitude. The outcomes demonstrate that while both methods accurately capture the primary effect of caisson depth on surface and subsurface soil settlements, the NN approach exhibits superior prediction accuracy. These methods are developed in a form amenable for routine design use in industry and have the potential for broader applicability in other design scenarios, such as building damage assessment and risk-assessment exercises.

Experimental study on flexural behaviours of fresh or aged hollow reinforced concrete girders strengthened by prestressed CFRP plates

The paper presents a well-rounded experimental study on the flexural performance of Reinforced Concrete (RC) box girders strengthened with prestressed carbon fibre reinforced polymer (CFRP) plates. The motivation behind the study was twofold: the rising need for structural reinforcement of existing aged and heavily utilised hollow RC box girders, and the absence of prior attempts to integrate prestressed CFRP plate strengthening for those hollow girders. Previous experimental studies are scarce and fewer studies are focused on the combined prestress and thin-wall effects, such as prestress-related stress condensation and shear lag. However, experimental results are important in directing further analytical studies for hollow sections with more complex behaviours than solid sections since there is a need to predict the behaviour of the prestress-strengthened hollow RC structures for routine design. This pivotal experimental study aims to quantify the structural interactions initiated by prestress in hollow sections and evaluate the impact of age while promoting further analytical initiatives. In this study, two types of CFRP plates, ordinary CFRP and steel-wire-CFRP (SW-CFRP), were used on different specimen beams with varying prestressing levels, sizes of the CFRP plates, and pre-damaged states representing aged and over-used members. Their performance indexes, including cracking load, yield load, ultimate load, structural stiffness, ductility, and crack resistance, were tested and summarised in this paper. The CFRP plates of the eight specimen beams were prestressed to different levels (non-prestressed, and 30% and 40% of the CFRP plate's ultimate strength). The test results suggest that the crack load increased by 86% and 134%, when the specimens were enhanced with the combinations of 30% prestress level for the same CFRP cross-section, and 40% prestress level with a thicker CFRP plate, respectively. The flexural capacity also increased by 42% and 72%, and flexural stiffness increased by 3% and 63%, respectively. The experimental results proved that the proposed prestressed CFRP plate technology effectively strengthens the new or aged RC box girders, but the ductility is sacrificed. These first-hand test results provide an excellent target dataset for further development in the analysis and design of prestressed CFRP plate-strengthened RC box girders.

Applications of Artificial Intelligence in Graphic Design

If the Industrial Revolution has enabled the replacement of humans with machines, the digital revolution is moving towards replacing our brains with artificial intelligence, so it is necessary to consider how this radical transformation affects the graphic design ecosystem. Hence, the research problem emerged (what are the effects of artificial intelligence on graphic design) and the research aimed to know the capabilities and effects of artificial intelligence applications in graphic design, and the study dealt in its theoretical framework with two main axes, the first is the concept of artificial intelligence, and the second is artificial intelligence applications in graphic design. The descriptive approach adopted a method of content analysis to analyze three research samples to reach a number of results and conclusions, including:1- Due to the employment of artificial intelligence in graphic design, it has facilitated the designer's work in some routine design aspects and made him focus on the creative aspects of design more broadly.2- 2- As a result of the rapid scientific progress, the issue of creative awareness when applying artificial intelligence will be a temporary problem that can be overcome in the future and will accelerate the creative competition between it and the graphic designer

Evaluation of the Impact of Buffer Management Strategies on Biopharmaceutical Manufacturing Process Mass Intensity

There is an increasing demand to improve the overall sustainability of the biopharmaceutical industry. A barrier to improvement has been the limited research undertaken in the area of environmental impact of key design decisions. The aim of this study was to perform a comprehensive evaluation of the impact of buffer management strategy and technology selection on overall process efficiency using process mass intensity (PMI) as a metric for comparison. The environmental impact of buffer management has yet to be fully understood, despite buffers being one of the most resource-intensive aspects of biopharmaceutical manufacturing. A detailed process model was used to evaluate the impact of buffer management on a monoclonal antibody (MAB) process at the 2000 L scale. This was achieved by means of a non-replicated full factorial design composed of six variables: product titre, quantity of unique buffers, preparation frequency, single-use threshold and equipment cleaning duration with two levels and buffer preparation strategy type with four levels. The study identified that buffer management has a critical impact on overall process mass intensity, demonstrating a possibility to achieve a reduction in PMI of up to 90% for the best scenario compared to the worst. The findings also indicated that single-use systems are greatly superior to stainless-steel systems in terms of overall process efficiency, which is consistent with established thinking. The results from this research represent a further significant step towards achieving a more sustainable biopharmaceutical industry, establishing buffer management as a critical focus area, quantifying the influence of key variables on process mass intensity and highlighting the benefits of using a process mass intensity metric as part of routine biopharmaceutical design.

Class A Prediction Symposium on Debris Flow Impact Forces on Single and Dual Barriers

Over recent years, significant advances have been made in the modelling of the impact dynamics between debris flows and single and dual rigid and flexible barriers. Numerical tools and analytical formulations have been proposed to predict the impact force, runup height, barrier deformation, and overflow and landing dynamics. However, there remains a dearth of well-recognised tools that can be used in routine engineering design practice because their reliability is unclear. On 8 and 9 May 2022, a virtual Class A Prediction Symposium on Debris Flow Impact Forces on Single and Dual Barriers was held to evaluate the reliability of existing design tools and identify areas for improvement to advance the current state of barrier design. The symposium was organised by The Hong Kong University of Science and Technology, Norwegian University of Science and Technology, Institute of Mountain Hazards and Environment of the Chinese Academy of Sciences, and the Geotechnical Engineering Office of the Civil Engineering and Development Department of the HKSAR Government. This paper summarises the existing research on flow-barrier interaction, and details of the symposium, including the prediction cases and results, roundtable discussion, and future research directions.

The transformation matrix in the 7DOFs beam formulation

A non-negligible percentage of steel products for civil and industrial constructions is realised with members characterised by a mono-symmetric cross-section. The non-coincidence between the centroid and the shear centre reflects in a quite complex behaviour that is remarkably influenced by the warping effects. Usually, frame design is based on the output data of commercial Finite Element Analysis Packages (FEAPs) but only few of them offer a refined beam element formulation able to reproduce the response of non-bisymmetric cross-section members (like the 7 degrees of freedom, DOFs, beam element). As a consequence, warping effects are usually neglected in routine design, leading in several cases to assess non-correct internal stresses, global displacements and critical buckling multipliers.This paper is focussed on mono-symmetric cross-section members and deals with the influence of the interaction between axial force, bending moments and bimoment in linear elastic range. In particular, the two strategies that FE developers usually adopt, in the 7 DOFs beam formulation, to pass from the local to the global reference system are herein shortly introduced and discussed. The effects of the associated transformation matrices have been investigated in few examples, also reproduced via closed expressions derived from the mixed torsion theory and FE shell models. Paper outcomes show that the results in terms of generalised displacements, internal forces and, consequently, stress distribution along the member cross-section are significantly different, strictly depending on the adopted transformation matrix. The importance of a correct evaluation of the bimoment distribution is stressed also by the fact that the new edition of the EN1993-1-1, expected in the next months, includes also the bimoment contribution for member checks.

Bond-slip at anchorage under unidirectional and bidirectional seismic excitation: Search for an efficient mathematical model

Reinforcement anchorage slip can significantly contribute to the seismic response of bridge columns, especially to residual deformation. For a reliable numerical model of slip action, the present study evaluates three advanced models, each founded on distinct principles: (a) a macroscopic model (M−I), (b) a microscopic model (M−II), and (c) a mixed model that employed micro-model material properties derived from a macro-model (M−III). The performance of each model under unidirectional shaking has been first validated. The M−I cannot account for bidirectional loading, and as such, the performance of the M−II and M−III has, for the first time, been rigorously examined against the two-component shake table test results. Beginning with the simplified pulses, the responses of representative bridge columns are computed to unidirectional and bidirectional shaking for several near-fault motions. The M−I, M−II, and M−III are fairly similar in mimicking the slip action for unidirectional loading. Also, the M−II and M−III can closely represent the responses to bidirectional shaking. A simple extension of the M−I is proposed to capture the effects of bidirectional loading. The performance of the M−I (extended), M−II, and M−III are shown similar from the viewpoint of representing (i) the seismic fragilities, (ii) the uncertainties of the influential parameters, and (iii) the consequences of a sequence of motions. The detailed scrutiny of a range of models helps select the most appropriate scheme in a specific design context. On the other hand, the less-rigourous model, viz., M−I with the proposed extension, can be used within the limitations of commercial software and can prove useful in routine design for bidirectional seismic action.

The Efficiency of the Benefits of Tire-Derived Aggregate Backfill for Buried Concrete Pipes Beneath Paved and Unpaved Roads

Tire-derived aggregate (TDA) has been proposed in recent studies to be considered as part of backfill soil to reduce stress and strain developed in buried pipes. However, little attention is paid to checking the influence of TDA on the behavior of concrete pipes buried under trafficked roads. This research studies this topic using a verified numerical model that considers the three-dimensional nature of traffic load effects. Different road sections were considered in the analyses to cover the effect of the presence of the pavement layer and the effect of the thickness of the base and subbase materials. The results revealed that the presence of TDA decreases the bending moment induced in the pipe wall. However, the TDA performance was found to be remarkably influenced by burial depth, and it increases as the burial depth decreases. Furthermore, the TDA influence for pipes with outer diameters of 1.49 m and 2.89 m is much lower than that of 0.41 m and 0.79 m. Importantly, it was found that the highest reduction in the bending moment was achieved for the 1.0 m burial depth. The results of this research provide insight into the performance of TDA and, thus, will help practitioners make a decision regarding the use of TDA in the routine design of buried concrete pipes.

P-450 Prediction models for estimating treatment independent conception in unexplained infertility – a systematic review

Abstract Study question What are the best prediction models which can estimate the chance of natural conception in couples with unexplained infertility? Summary answer The best quality clinical prediction models were those generated by Hunault et al (2004), Van Eekelen et al (2017) and McLernon et al. (2019). What is known already Although couples with unexplained infertility have a chance of natural conception, a formal estimate of prognosis is not part of routine clinical decision making in most settings. In the UK, NICE recommends IVF after two years of unexplained infertility in all couples, regardless of their individual chances of conception without treatment. This approach risks overtreatment for some whilst delaying access to IVF for others. Since the last systematic review on this topic 10 years ago, several models which aim to predict natural conception in infertile couples have been published, but few are in routine clinical use Study design, size, duration We searched OVID MEDLINE, OVID EMBASE, and OVID PsycINFO systematically for primary articles published between 1978 and 2022, reporting on the development and/or validation of models in predicting spontaneous conception, pregnancy, or live birth. No language or any other restrictions were applied. Participants/materials, setting, methods We included couples with unexplained infertility / those with no major barriers to natural conception. Women who underwent any form of fertility treatment immediately after the initial diagnostic work up were excluded. The methodological quality of the included papers was assessed using criteria within the CHARMS checklist. Risk of bias was evaluated using the PROBAST tool while discrimination and calibration results, which rate the performance of the prediction model, were also reported. Main results and the role of chance Eighteen publications reported on 23 prediction models with natural conception, pregnancy, ongoing pregnancy and live birth as outcomes. Of 11 studies involving model development, internal and external validation were reported in 4 and 2 publications respectively . Two studies published extended versions of the same model (Hunault et al, 2004) while 3 studies focussed on independent validation of existing models. The methodological rigour of the models has improved over time, as demonstrated by accuracy measures including discrimination and calibration. Three models (Hunault et al, 2004, Van Eekelen et al, 2017, and McLernon et al, 2019) had low risk of bias. The static Hunault model can be used to determine the chance of conception at a single point in time – usually at the conclusion of the initial fertility work up, whereas the Van Eekelen and McLernon models are dynamic models that can estimate chances of conception at different time points. The discriminatory ability of models ranged between 0.59-0.64 in the internal validation and external validation studies. The calibration slope for the Hunault’s static model was 0.6 to 1.0 and for the dynamic models it ranged from 0.62 to 1.01 for Van Eekelen’s model and 0.65to 1.06 for McLernon’s model. Limitations, reasons for caution The quality of prediction models which predated the CHARMS checklist and PROBAST tool could not be adequately assessed. The population with most models went beyond unexplained infertility and included other couples with a chance of natural conception e.g. mild male infertility and minimal endometriosis. Wider implications of the findings Of the 3 models which are of high quality, the Hunault model can only be used once but the Van Eekelen and McLernon models have the potential to be used more flexibly, following further external validation in different settings and larger populations. Trial registration number not applicable