Engineering Judgment Research Articles

Methodology for determination of seismic force modification factors in Canada: Performance-based unified procedure

The National Building Code of Canada (NBC) employs seismic force modification factors (i.e. ductility-related factor, Rd, and an overstrength-related factor, Ro) for different Seismic Force Resisting Systems (SFRSs), which, since 2005, are largely based on engineering judgment and qualitative comparisons of seismic response characteristics of different SFRSs. Currently, there is no unified procedure in Canada for systematically quantifying these values, which has potentially led to perceived inconsistent levels of performance between buildings built with different SFRSs. While some research has been carried out in Canada to quantitatively evaluate the seismic response of different SFRSs using the FEMA P695 methodology with some modifications, inconsistencies exist among different research works. Moreover, the number of archetypes developed in these studies was limited, due to the computationally laborious incremental dynamic analysis (IDA) step in FEMA P695. Therefore, there is a need for a consistent and efficient methodology for structural performance assessment of different SFRSs in Canada. The proposed performance-based unified (PBU) procedure is to systematically quantify Rd and Ro factors for different SFRSs in the NBC. The PBU procedure is designed to be a performance-based approach (vs the risk-based approach of FEMA P695). In addition, our procedure is devised to optimize the number of archetypes through a two-level screening procedure using a nonlinear pushover and time history analyses before running the IDA. To validate the PBU procedure, we developed 21 different concrete moment frame archetypes covering various key parameters. The results verify the efficiency of the screening feature of the PBU procedure by a significant reduction in the number of archetypes requiring IDA.

The Allegory of the Rock Engineering Cave

Geoscientists and engineers are part of a system that produces changes to the world we live in. As machines are expected to gradually replace humans in various technical tasks (e.g., data collection and data characterisation), it becomes crucial to apply critical thinking and to question the foundations of commonly accepted practices. The challenge is to accept that empirical methods are shaped by cognitive biases, which result from our mind interpreting data by a process of data simplification. Indeed, it is possible to draw an analogy between rock engineering methods and Plato’s Allegory of the Cave. The fire casting the shadows along the cave walls represents the process of quantification of qualitative assessments of commonly accepted data collection methods. The chains holding the engineers as prisoners in the cave are empirical methods accepted as industry standards despite important limitations. Engineering judgment alone will not allow engineers to break free of those chains, and to emerge from the confined spaces of the cave and see things for what they really are (i.e., introduce truly objective data collections methods that better reflect failure mechanisms). In this paper the authors use philosophical arguments to justify the need to “dequantify” the GSI classification system and to teach us that engineering design should always be driven by the important questions of how, why, and whether.

Closure to “Evaluating Uncertainty Associated with Engineering Judgement in Predicting the Lateral Response of Conductors” by M. Guevara, J. P. Doherty, C. Gaudin, and P. G. Watson

Closure to “Evaluating Uncertainty Associated with Engineering Judgement in Predicting the Lateral Response of Conductors” by M. Guevara, J. P. Doherty, C. Gaudin, and P. G. Watson

Discussion of “Evaluating Uncertainty Associated with Engineering Judgement in Predicting the Lateral Response of Conductors” by M. Guevara, J. P. Doherty, C. Gaudin, and P. G. Watson

Discussion of “Evaluating Uncertainty Associated with Engineering Judgement in Predicting the Lateral Response of Conductors” by M. Guevara, J. P. Doherty, C. Gaudin, and P. G. Watson

Assessing Risk, Effectiveness, and Benefits in Transportation Regulation

AbstractWe review the practice of safety benefits analysis for federal transportation regulations in the USA. Using a case-study approach, we explore the linkages between risk assessment and benefits analysis, adding to previous work exploring these linkages for environmental health regulations. Challenges for calculating the benefits of transportation safety regulations arise because safety outcomes, like many noncancer health effects, typically do not have formal risk relationships like dose–response functions established for them. Analysts often rely on engineering or other expert judgments or resort to qualitative discussions to connect a regulatory intervention to its intended outcome. Challenges also arise when regulatory outcomes are intangible or do not have established metrics. Safety outcomes are not always measurable in concrete terms like mortality risk and may include difficult-to-operationalize concepts like “safety culture.” If the outcome is not measurable, then quantifying or monetizing the expected effects of a regulation is not possible, and the ability to conduct robust qualitative discussions also may be limited. Economists evaluating benefits for safety regulations encounter limitations analogous to difficulties found in health regulations. To inform policymaking effectively, economists and safety experts could look to the relationship developed in environmental economics between economists and health scientists.

A Hands-on Guided-inquiry Materials Laboratory that Supports Student Agency

Under the new ABET accreditation framework, students are expected to demonstrate “an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.” Traditional, recipe-based labs provide few opportunities for students to engage in realistic experimental design or develop a sense of agency, and research has cast […]

Open issues on non-linear modelling for seismic assessment of existing masonry buildings

The difficulties on the assessment of the seismic capacity of existing masonry buildings through non-linear FEM analyses have been examined in this paper, in the framework of the equivalent frame modeling. A significant problem lies in identifying an adequate equivalent frame idealization of the walls, i.e., capable of providing an acceptable response of the numerical model. Indeed, the geometrical complexity characterizing real masonry buildings, often due to irregular distribution of the wall openings, leads to choices and expedients which are impossible to codify and may only be defined on a case-by-case basis. Consequently, an adequate engineering judgment, which must obviously be considered when the results are being interpreted, is required.Linear and non-linear analysis were adopted on equivalent frame schemes of existing walls highlighting the problems of identifying geometric patterns, as well as defining the mechanical model of the spandrels or the influence of connection degree between orthogonal walls on the seismic behavior. In this paper some possible solutions to the problems are proposed, also with reference to specific study cases.

Seismic demand on non‐structural elements for quantifying seismic performance factors

AbstractThe quantification of non‐structural seismic performance factors is a crucial step to improve the seismic performance of non‐structural elements (NSEs). Non‐structural seismic performance factors currently included in modern seismic design provisions are mainly based on engineering judgment and have not been calibrated to meet specific performance objectives. This makes the seismic performance of NSEs designed according to force‐based procedures uncertain at best. Previous studies have proposed a general framework for the quantification of non‐structural seismic performance factors. However, due to the necessity of considering the supporting structure dynamic properties in the estimation of the seismic demand, the required computational overhead can make the process unfeasible in some cases depending on the target supporting structure population and the pursued performance objectives. This paper proposes a procedure to estimate the seismic demand on NSEs for the quantification of non‐structural seismic performance factors that drastically reduces the required computational overhead. The proposed procedure makes use of synthetic floor accelerograms to describe in terms of seismic demand an entire population of supporting structures and ground motion sets. The proposed procedure is validated against a complete multiple‐stripe non‐linear time history analysis by deriving and comparing fragility curves. The results of the validation demonstrate that the proposed procedure is able to derive fragility curves that closely match the ones generated by using a multiple‐stripe analyses with remarkable savings in computational time and output storage size.

Rock point load test (PLT index) and its correlation with rock coring rate of bored pile machine

Rock socketed cast in-situ bored pile has getting more common in the local foundation industry due to high load carrying capacity to support the increasingly large superstructure load. The estimation of bored pile production rate based on rock strength is vital for piling contractor in terms of project planning, site work done forecasting and management of resources. Uniaxial compressive strength (UCS) of rocks is a useful parameter needed for analytical and designing purpose for rock structure, as well as classification of rock strength. Owing to the time-consuming, tedious and expensive testing procedure of UCS, point load test (PLT) on irregular lump samples has appeared to be the best alternative test to ascertain rock strength, which can be performed on-site or off-site. This research was conducted to establish the correlation between rock PLT index and rock coring rate of bored pile machine, where the PLT results and rock coring data were collected from manual recording at respective project site. Graphical relationship was derived for PLT index against rock coring rate for several pile size categories. As rock UCS is typically adopted for foundation design purpose, the conversion factor between PLT index and UCS was derived for the typical bedrock formation encountered in Kuala Lumpur, namely Granitic rock and Limestone. This study also depicts the estimation of mobilized rock unit shaft friction with respect to the corresponding UCS value, using a recommended empirical formula. From this research study, it was justified that PLT could serve as a cost-effective and straightforward field test which provides invaluable guidance for piling production rate estimation as well as better engineering judgement in foundation design.

The Benefit of Informed Risk-Based Management of Civil Infrastructures

One of the most interesting applications of Structural Health Monitoring (SHM) is the possibility of providing real-time information on the conditions of civil infrastructures during and following disastrous events, thus supporting decision-makers in prompt emergency operations. The Bayesian decision theory provides a rigorous framework to quantify the benefit of SHM through the Value of Information (VoI) accounting for different sources of uncertainties. This decision theory is based on utility considerations, or, in other words, it is based on risk. Instead, decision-making in emergency management is often based on engineering judgment and heuristic approaches. The goal of this paper is to investigate the impact of different decision scenarios on the VoI. To this aim, a general framework to quantify the benefit of SHM information in emergency management is applied to different decision scenarios concerning bridges under scour and seismic hazards. Results indicate that the considered decision scenario might tremendously affect the results of a VoI analysis. Specifically, the benefit of SHM information could be underestimated when considering non-realistic scenarios, e.g., those based on risk-based decision-making, which are not adopted in practice. Besides, SHM information is particularly valuable when it prevents the selection of suboptimal emergency management actions.

Battle of the Leakage Detection and Isolation Methods

A key challenge in designing algorithms for leakage detection and isolation in drinking water distribution systems is the performance evaluation and comparison between methodologies using benchmarks. For this purpose, the Battle of the Leakage Detection and Isolation Methods (BattLeDIM) competition was organized in 2020 with the aim to objectively compare the performance of methods for the detection and localization of leakage events, relying on supervisory control and data acquisition (SCADA) measurements of flow and pressure sensors installed within a virtual water distribution system. Several teams from academia and the industry submitted their solutions using various techniques including time series analysis, statistical methods, machine learning, mathematical programming, met-heuristics, and engineering judgment, and were evaluated using realistic economic criteria. This paper summarizes the results of the competition and conducts an analysis of the different leakage detection and isolation methods used by the teams. The competition results highlight the need for further development of methods for leakage detection and isolation, and also the need to develop additional open benchmark problems for this purpose.

Theorizing Engineering Judgment at the Intersection of Decision-Making and Identity

Engineering judgment is critical to both engineering education and engineering practice, and the ability to practice or participate in engineering judgment is often considered central to the formation of professional engineering identities. In practice, engineers must make difficult judgments that evaluate potentially competing objectives, ambiguity, uncertainty, incomplete information, and evolving technical knowledge. Nonetheless, while engineering judgment is implicit in engineering work and so central to identification with the profession, educators and practitioners have few actionable frameworks to employ when considering how to develop and assess this capacity in students. In this paper, we propose a theoretical framework designed to inform both educators and researchers that positions engineering judgment at the intersection of the cognitive dimensions of naturalistic decision-making, and discursive dimensions of identity. Our proposed theory positions engineering judgment not only as an individual capacity practiced by individual engineers alone but also as the capacity to position oneself within the discursive community so as to participate in the construction of engineering judgments among a group of professionals working together. Our theory draws on several strands of existing research to theorize a working framework for engineering judgment that considers the cognitive processes associated with making judgments and the inextricable discursive practices associated with negotiating those judgments in context. In constructing this theory, we seek to provide engineering education practitioners and researchers with a framework that can inform the design of assignments, curricula, or experiences that are intended to foster students’ participation in the development and practice of engineering judgment.

Extratropical cyclone damage to the seawall in Dawlish, UK: eyewitness accounts, sea level analysis and numerical modelling

The February 2014 extratropical cyclonic storm chain, which impacted the English Channel (UK) and Dawlish in particular, caused significant damage to the main railway connecting the south-west region to the rest of the UK. The incident caused the line to be closed for two months, £50 million of damage and an estimated £1.2bn of economic loss. In this study, we collate eyewitness accounts, analyse sea level data and conduct numerical modelling in order to decipher the destructive forces of the storm. Our analysis reveals that the disaster management of the event was successful and efficient with immediate actions taken to save lives and property before and during the storm. Wave buoy analysis showed that a complex triple peak sea state with periods at 4–8, 8–12 and 20–25 s was present, while tide gauge records indicated that significant surge of up to 0.8 m and wave components of up to 1.5 m amplitude combined as likely contributing factors in the event. Significant impulsive wave force of up to 286 KN was the most likely initiating cause of the damage. Reflections off the vertical wall caused constructive interference of the wave amplitudes that led to increased wave height and significant overtopping of up to 16.1 m3/s/m (per metre width of wall). With this information and our engineering judgement, we conclude that the most probable sequence of multi-hazard cascading failure during this incident was: wave impact force leading to masonry failure, loss of infill and failure of the structure following successive tides.

Method of determining the exponent in the formula to predict yielding and maximum capacity under combined stress for bending moment‐resisting joints with drift‐pins

AbstractAn engineering judgment is often used to determine the exponent of the verification formula for combined stresses applied to moment‐resisting joints using drift‐pins. In this study, the exponent was determined based on a mechanical model. (1) The exponent of the verification formula for moment‐resisting joints with drift‐pins subjected to combined stresses was theoretically derived considering the effect of the grain angle given by Hankinson's formula. (2) The combined stress verification formula was validated by numerical analyses, experiments, and past experimental studies. It was confirmed that the method of determining the exponent in this formula is reasonable.

A Design Method for Storage Capacity of Rainwater Harvesting Considering Economic Effectiveness

The use of rainwater harvesting facilities is increasing in accordance with national laws, institutional regulations, and administrative support from local governments in Korea. However, most of the plans for storage capacity of rainwater harvesting are characterized by institutional constraints and determined by the judgment of engineers. This study aimed to suggest a method for economically determining the storage capacity of rainwater harvesting. The study presented a mass balance equation that can evaluate rainwater reuse amount according to the size of rainwater harvesting, and then defined the cost and benefit factors for the installation and operation of rainwater harvesting. Net present value (NPV) and benefit–cost ratio (BCR) were used to analyze the economic effectiveness for each storage capacity of rainwater harvesting. The proposed method was applied to the rainwater harvesting in Cheongna District in Incheon, and the NPV was found appropriate for the evaluation of the economic effectiveness. According to the design report, for the rainwater harvesting planned to be 6,740 m<sup>3</sup>, the NPV was calculated to be −478 million KRW for a 30-year design life. Meanwhile, the optimal size considering economic effectiveness was 2,000 m<sup>3</sup>, and the NPV of the size was analyzed to be +1,738 million KRW. Therefore, economic analysis is suitable as an alternative to determine the appropriate size of rainwater harvesting.

Statistical Treatments of Chloride Threshold and Corrosion Propagation Rate

The variability found in real structures is a function of the “intrinsic” variability of the material itself, of its aging with time and of the external climatic conditions, and, therefore, it is normal that the chloride threshold and the corrosion rates could vary spatially in the same structure or temporarily as the concrete ages. In present communication, some statistical distributions of chloride threshold are discussed, as well as the variability of the corrosion rate in real exposure conditions. In all both cases, the values found in laboratory specimens are in the same range than those found in real structures. The chloride threshold can vary from 0.2% to around 3% by weight of cement depending on the corrosion potential, which, in turn, depends on the particular condition of the steel bar in each structure. The corrosion rates show to be below 0.1 µA/cm2 when the steel is passive and values above 1 µA/cm2 are seldom found in real structures. The high variability when considering all choices may impact in a prediction of residual life of several decades of difference which aims into the need for the assessment of a specialized engineering judgement in function of the quality of the concrete and the exposure class.

An Integrated Framework for the Quantification of Road Network Seismic Vulnerability and Accessibility to Critical Services

Road networks are regarded as the backbone of transportation systems, which play an important role in the social and economic prosperity of societies. Due to this reason, it is crucial to develop road networks with higher resiliency rates to operate normally during earthquake incidents. In the last decades, the research that tackled the management of disasters for road networks gained great attention, in particular by developing various seismic vulnerability assessment models. Most of those models study a single criterion, e.g., physical damage of road assets, traffic disruption, and/or functionality loss of the network without taking into consideration the combination of different vulnerability criteria. The proposed framework is part of the global seismic vulnerability assessment models that combine fragility functions and vulnerability indices, which is demonstrated by an application in a road network in the city of Penang in Malaysia. In the first step, the fragility functions are developed where their results are used to calculate the Seismic Vulnerability Index (SVI) for roadways by weighting the main investigated parameters. This is followed by investigating the Accessibility Index (AI) model that is employed to assess the accessibility of targeted districts within the investigated area. Subsequently, an integrated approach is employed to generate the emergency evacuation maps to critical service centres by referring to the correlations between vulnerability and the accessibility rates. In conclusion, the results of this study integrate engineering judgment and numerical models to create a comparative study for assessing the performance of road networks and to validate the significance of an integrated seismic assessment on various critical societal sectors, such as improving emergency accessibility and implementing better mitigation strategies for communities living in disaster-prone areas.

Depth‐damage curves for rail rapid transit infrastructure

AbstractEstimates of flood‐related damages and costs often rely on asset‐specific depth‐damage curves that characterize the fragility of a given asset. To date, there are very few depth‐damage curves that are potentially applicable to rail rapid transit infrastructure, and no studies attempt to construct these relationships specifically these asset classes. Given the lack of empirical performance data or asset‐specific reliability tests, we solicited expert engineering judgment to characterize the fragility of transit assets to saltwater flood exposure. We validate the resulting synthetic depth‐damage relationships via a benchmarking approach and demonstrate consistency with previously published depth‐damage curves for similar asset classes. The solicitation framework presented can easily be extended to other infrastructure assets and systems, potentially serving as a key step toward a more rigorous quantification of the potential risks posed to infrastructure by natural hazards and climate change.

A method to find the optimum routes and stations for bus rapid transit in urban areas

Public transportation (PT) is an essential system for cities to achieve sustainability. However, determination of proper locations for PT stations and finding suitable routes are critical decisions. The aim of the present study is to propose a novel method to determine bus rapid transit (BRT) stations and routes in cities, using a fuzzy inference system (FIS) and binary integer programming (BIP). In the proposed method, first, a set of potential locations for BRT stations is selected based on engineering judgement. Then, by considering several variables and with the help of FIS, a weight is calculated for each location. Subsequently, the optimum corridors for BRT are identified with BIP. The objective function of the BIP model is to maximise the sum of the stations’ weights (involving the most suitable locations for BRT stations), while ensuring that the maximum number of passengers can travel each route. Constraints related to technical, social and economic considerations are also taken into account. To control the model efficiency, the outputs are compared with the stations and corridor suggested by experts. Based on the results, the most important features of the developed model are its simplicity, its ability to consider various factors, a short running time and its high level of accuracy.

Machine Learning-Aided Microdroplets Breakup Characteristic Prediction in Flow-Focusing Microdevices by Incorporating Variations of Cross-Flow Tilt Angles

Controlling droplet breakup characteristics such as size, frequency, regime, and droplet quality within flow-focusing microfluidic devices is critical for different biomedical applications of droplet microfluidics such as drug delivery, biosensing, and nanomaterial preparation. The development of a prediction platform capable of forecasting droplet breakup characteristics can significantly improve the iterative design and fabrication processes required for achieving desired performance. The present study aims to develop a multipurpose platform capable of predicting the working conditions of user-specific droplet size and frequency and reporting the quality of the generated droplets, regime, and hydrodynamical breakup characteristics in flow-focusing microdevices with different cross-junction tilt angles. Four different neural network-based prediction platforms were compared to accurately estimate capsule size, generation rate, uniformity, and circle metric. The trained capsule size and frequency networks were optimized using the heuristic optimization approach for establishing the Pareto optimal solution plot. To investigate the transition of the droplet generation regime (i.e., squeezing, dripping, and jetting), two different classification models (LDA and MLP) were developed and compared in terms of their prediction accuracy. The MLP model outperformed the LDA model with a cross-validation measure evaluated as 97.85%, demonstrating that the droplet quality and regime prediction models can provide an engineering judgment for the decision maker to choose between the suggested solutions on the Pareto front. The study followed a comprehensive hydrodynamical analysis of the junction angle effect on the dispersed thread formation, pressure, and velocity domains in the orifice.