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The auditing and accounting profession must provide appropriate disclosure of the going concern status of an entity, especially when that status is threatened. Auditors have an obligation to consider the wider legal environment of an entity, including all relevant case law, when they perform any such audit. Despite this obligation, the auditing profession appears to violate important legal principles. The auditor’s approach to the going concern status of an entity is contained in the South African Auditing Standard, SAAS 570 “Going Concern”. The South African legal framework’s approach to this issue emerges from the Supreme Court case Philotex (Pty) Ltd v Snyman. This article explores the fundamental disagreement between the auditor’s approach to the going concern problem and that adopted in terms of the wider South African legal framework.

An understanding of uncertainty has always been an integral part of property valuations. No valuation is certain, and the valuer needs to convey to the user of the valuation in the degree of uncertainty pertaining to the market value.

This practice briefing is a short overview of the importance of understanding uncertainty in valuation in normal markets and the particular difficulties now with the material uncertainty created by the COVID-19 pandemic.

This paper discusses how important it is for the valuer and the client to communicate and understand the uncertainty in the market at any point of time. The COVID-19 has had a significant impact on property values and the importance of clarity within valuation reports.

This paper looks at the importance of placing capital and rental value changes due to material uncertainty in valuation reports.

This provides guidance on how professional bodies are advising their members, around the world, on how to report valuations and market value in the context of material uncertainty.

Manufacturing processes, such as laminations, may introduce uncertainties in the magnetic properties of materials used in electrical machines. This issue, together with magnetization errors, can cause serious deterioration in the performance of the machines. Hence, stochastic material models are required for the study of the influences of the material uncertainties. The purpose of this paper is to present a methodology to study the impact of magnetization pattern uncertainties in permanent magnet electric machines.

The impacts of material uncertainties on the performances of an interior permanent magnet (IPM) machine were analyzed using two different robustness metrics (worst-case analysis and statistical study). In addition, two different robust design formulations were applied to robust multi-objective machine design problems.

The computational analyses show that material uncertainties may result in deviations of the machine performances and cause nominal solutions to become non-robust.

In this paper, the authors present stochastic models for the quantification of uncertainties in both ferromagnetic and permanent magnet materials. A robust multi-objective evolutionary algorithm is demonstrated and successfully applied to the robust design optimization of an IPM machine considering manufacturing errors and operational condition changes.

The purpose of this paper is to develop an analytical approach to evaluate the influence of material uncertainties on cross‐sectional stiffness properties of thin walled composite beams.

Fuzzy arithmetic operators are used to modify the thin‐walled beam formulation, which was based on a mixed force and displacement method, and to obtain the uncertainty properties of the beam. The resulting model includes material uncertainties along with the effects of elastic couplings, shell wall thickness, torsion warping and constrained warping. The membership functions of material properties are introduced to model the uncertainties of material properties of composites and are determined based on the stochastic behaviors obtained from experimental studies.

It is observed from the numerical studies that the fuzzy membership function approach results in reliable representation of uncertainty quantification of thin walled composite beams. The propagation of uncertainties is also demonstrated in the estimation of structural responses of composite beams.

This work demonstrates the use of fuzzy approach to incorporate uncertainties in the responses analytically, in turn improving computational efficiency drastically as compared to the Monte‐Carlo method.

The purpose of this study is to explore how demolition contractors coordinate project activities for buildings at their end-of-life. The organizations are thereby conceptualized as information processing systems facing uncertainty.

A multiple-case study methodology was selected to gain in-depth insights from three projects with different end-of-life strategies: a faculty building (material recycling), a nursing home (component reuse) and a psychiatric hospital (element reuse). Using a theory elaboration approach, the authors sought to explain how and why demolition contractors process information for end-of-life coordination.

End-of-life strategies differ in the degree of building, workflow and environmental uncertainty posed to the demolition contractor. Whether or not a strategy is effective depends on the (mis)match between the specific levels of uncertainty and the adopted coordination mechanisms.

The explanatory account on end-of-life coordination refines information processing theory for the context of (selective) demolition projects.

The detailed case descriptions and information processing perspective enable practitioners to select, implement and reflect on coordination mechanisms for demolition/deconstruction projects at hand.

Reflecting its dual conceptual-empirical and inductive-deductive focus, this study contributes with new opportunities to explain building end-of-life coordination with a refined theory.

The purpose of this study is to enable performing reliability-based design optimisation (RBDO) for a composite component while accounting for several multi-scale uncertainties using a large representative volume element (LRVE). This is achieved using an efficient finite element analysis (FEA)-based multi-scale reliability framework and sequential optimisation strategy.

An efficient FEA-based multi-scale reliability framework used in this study is extended and combined with a proposed sequential optimisation strategy to produce an efficient, flexible and accurate RBDO framework for fibre-reinforced composite laminate components. The proposed RBDO strategy is demonstrated by finding the optimum design solution for a composite component under the effect of multi-scale uncertainties while meeting a specific stiffness reliability requirement. Performing this using the double-loop approach is computationally expensive because of the number of uncertainties and function evaluations required to assess the reliability. Thus, a sequential optimisation concept is proposed, which starts by finding a deterministic optimum solution, then assesses the reliability and shifts the constraint limit to a safer region. This is repeated until the desired level of reliability is reached. This is followed by a final probabilistic optimisation to reduce the mass further and meet the desired level of stiffness reliability. In addition, the proposed framework uses several surrogate models to replace expensive FE function evaluations during optimisation and reliability analysis. The numerical example is also used to investigate the effect of using different sizes of LRVEs, compared with a single RVE. In future work, other problem-dependent surrogates such as Kriging will be used to allow predicting lower probability of failures with high accuracy.

The integration of the developed multi-scale reliability framework with the sequential RBDO optimisation strategy is proven computationally feasible, and it is shown that the use of LRVEs leads to less conservative designs compared with the use of single RVE, i.e. up to 3.5% weight reduction in the case of the 1 × 1 RVE optimised component. This is because the LRVE provides a representation of the spatial variability of uncertainties in a composite material while capturing a wider range of uncertainties at each iteration.

Fibre-reinforced composite laminate components designed using reliability and optimisation have been investigated before. Still, they have not previously been combined in a comprehensive multi-scale RBDO. Therefore, this study combines the probabilistic framework with an optimisation strategy to perform multi-scale RBDO and demonstrates its feasibility and efficiency for an fibre reinforced polymer component design.

New applications of solid freeform fabrication (SFF) are arising, such as functional rapid prototyping and in situ fabrication, which push SFF to its limits in terms of geometrical fidelity due to the applications' inherent process uncertainties. Current closed‐loop feedback control schemes monitor and manipulate SFF techniques at the process level, e.g. envelope temperature, feed rate. “Closing the loop” on the process level, instead of the overall part geometry level, leads to limitations in the types of errors that can be detected and corrected. The purpose of this paper is to propose a technique called greedy geometric feedback (GGF) control which “closes the loop” on the overall part geometry level.

The overall part geometry is monitored throughout the print and, using a greedy algorithm, real‐time decisions are made to serially determine the locations of subsequent droplets, i.e. overall part geometry is directly manipulated. A computer simulator and a physical experimental platform were developed to compare the performance of GGF to an open‐loop control scheme. Root mean square surface height errors were measured under controlled uncertainties in droplet height, droplet radius of curvature, droplet positioning and mid‐print part deformations.

The GGF technique outperformed open‐loop control under process uncertainties in droplet shape, droplet placement and mid‐print part deformations. The disparity between performances is dependant on the nature and extent of the imposed process uncertainties.

Future research will focus on improving the performance of GGF for specific cases by designing more complex greedy algorithmic scoring heuristics. Also, the technique will be generalized beyond heightmap representations of 3D spaces.

The GGF technique is the first to “close the loop” on the overall part geometry level. GGF, therefore, can compensate for a broader range of errors than existing closed‐loop feedback control schemes. Also, since the technique only requires the real‐time update of a very limited set of heights, the technique is computationally inexpensive and widely applicable. By developing a closed‐loop feedback scheme that addressed part geometry‐level errors, SFF can be applied to more challenging in situ fabrication scenarios with less conventional materials.

The purpose of this paper is to examine how certain limitations of the current approaches to planning and scheduling of aircraft heavy maintenance can be addressed using a single integrated framework supported by unified data structures.

The “unitary structuring technique”, originally developed within the context of manufacturing planning and control, is further enhanced for aircraft heavy maintenance applications, taking into account the uncertainty associated with condition‐based maintenance. The proposed framework delivers the advanced functionalities required for simultaneous and dynamic forward planning of maintenance operations, as well as finite loading of resources, towards optimising the overall maintenance performance.

Execution of maintenance operations under uncertainty involves materials changes, rectification and re‐assembly. It is shown that re‐scheduling of materials (spare‐parts), resources and operations can be taken care of by simultaneous and dynamic forward planning of materials and operations with finite loading of resources, using the integrated framework.

As part of adopting the proposed framework in practice, it needs to be guided by an overall methodology appropriate for application‐specific contexts.

The potential direct benefits of adopting the proposed framework include on‐time project completion, reduced inventory levels of spare‐parts and reduced overtime costs.

Existing approaches to aircraft maintenance planning and scheduling are limited in their capacity to deal with contingencies arising out of inspections carried out during the execution phase of large maintenance projects. The proposed integrated approach is, capable of handling uncertainty associated with condition‐based maintenance, due to the added functionalities referred to above.

The recent coronavirus pandemic created uncertainty across most markets. This has resulted in many valuations being reported with caveats warning that they are uncertain. However, many valuers and their clients remain unclear as to what these warnings are supposed to convey and why they are required by many valuation standards, including the International Valuation Standards. The purpose of this paper is to explain how recognition of the need for uncertainty disclosures has developed over the past 25 years and how such disclosures can enhance overall trust in valuation.

The author has been involved in the development of the guidance issued by both the International Valuation Standards Council and Royal Institution of Chartered Surveyors, which included extensive consultation with financial regulators and valuation users alike. He has also examined the wider economic theories of risk and uncertainty and how these need to be clearly distinguished in valuations.

This paper identifies the situations under which valuation uncertainty can occur, and steps that a valuer can follow to determine whether it is sufficiently material to require an appropriate caveat to be issued alongside the valuation. It also examines the merits of different ways in which material uncertainty can be disclosed.

The paper should provide valuers with a better understanding of the reason why uncertainty disclosures are required and the circumstances in which they are required. It also provides principles to help them formulate disclosures that are appropriate in different circumstances.

This is an abridged version of a Valuers' Briefing “Valuation Uncertainty – Reporting the unknowable” by the author and published as either an eBook or paperback available from Amazon.

This paper aims to focus on the stochastic analysis of composite rotor blades with matrix cracking in forward flight condition.

The effect of matrix cracking and uncertainties are introduced to the aeroelastic analysis through the cross-sectional stiffness properties obtained using thin-walled beam formulation, which is based on a mixed force and a displacement method. Forward flight analysis is carried out using an aeroelastic analysis methodology developed for composite rotor blades based on the finite element method in space and time. The effects of matrix cracking are introduced through the changes in the extension, extension-bending and bending matrices of composites, whereas the effect of uncertainties are introduced through the stochastic properties obtained from previous experimental and analytical studies.

The stochastic behavior of helicopter hub loads, blade root forces and blade tip responses are obtained for different crack densities. Further, assuming the behavior of progressive damage in same beam is measurable as compared to its undamaged state, the stochastic behaviors of delta values of various measurements are studied. From the stochastic analysis of forward flight behavior of composite rotor blades at various matrix cracking levels, it is observed that the histograms of these behaviors get mixed due to uncertainties. This analysis brings out the parameters which can be used for effective prediction of matrix cracking level under various uncertainties.

The behavior is useful for the development of a realistic online matrix crack prediction system.

Instead of introducing the white noise in the simulated data for testing the robustness of damage prediction algorithm, a systematic approach is developed to model uncertainties along with damage in forward flight simulation.