Different Levels Of Conservatism Research Articles

Robust scheduling of a pulp and paper mill considering flexibility provision from steam power generation

The production scheduling and flexibility provision analysis are of great importance for industrial facilities to provide support for the main power grid. This study proposes a comprehensive scheduling model for an industrial pulp and paper (P&P) mill that considers the flexibility provision from steam power generation. In this model, the internal relationships between the production and consumption of electricity, steam, and pulp in the operational processes of the P&P mill are investigated. Meanwhile, the available flexibility of steam power generation is quantified and further enhanced for participation in the manual frequency restoration reserve (MFRR) market. Furthermore, a robust scheduling model that uses support vector clustering (SVC) technology is proposed to assess the impact of uncertainties in steam temperature and pressure on the available flexibility of steam power generation, thereby reducing the probability of failing to provide the contracted flexibility for MFRR. Simulation results demonstrate that the comprehensive scheduling model significantly increases the available flexibility of steam power generation for MFRR, resulting in a daily revenue increase of $1839.8. Moreover, a balance between the revenue obtained from the MFRR market and the probability of economic penalties incurred for failing to meet the contracted flexibility is achieved by comparing different levels of conservatism in the robust scheduling model.

Different approaches for stress index calculation in elbows of a fusion plant piping system

In the framework of the final verification for the mechanical assessment of a nuclear piping system, critical cross sections, which turned out to belong to an elbow, have been first selected: a study has been subsequently developed, focused on the evaluation of stress index and safety margins for primary stress, starting from what is set out by ASME B31.3 for Process Piping and by RCC-MRx design Code for mechanical components of nuclear installations. The aim was to move to the critical evaluation of the application of the approach “by rules” when finite elements analyses provide both results in terms of internal forces to obtain the nominal stress, and the detailed numerical evaluation of the local stress state and stress concentration. The results show the differences in stress computation that can be obtained by adopting the finite element modeling or by straight application of codes rules and allows to identify the different levels of conservatism and to choose the suitable criteria to be used in an elbow stress assessment.

Probing the stability landscape of cylindrical shells for buckling knockdown factors.

The buckling response of axially compressed cylindrical shells is well known for its imperfection sensitivity. Mapping out a stability landscape by localized probing has recently been proposed as a rational means for establishing shell buckling knockdown factors. Probing using a point force directed radially inwards and perpendicular to the cylinder wall is based on the insight that a localized single dimple exists as an edge state in the basin boundary of the stable prebuckling equilibrium. Here, we extend the idea of probing to bi-directional inwards and outwards forces to trigger both single-dimple and double-dimple edge states. We identify key features of the ensuing probing stability landscape and generalize these to derive three design curves of varying conservatism that are a function of the non-dimensional Batdorf parameter only. Interestingly, the most conservative of the three knockdown curves bounds a large dataset of experimental buckling results from below, despite being derived from probing features of geometrically perfect cylinders. Overall, the three design curves permit a more nuanced design approach than legacy knockdown factors, as different levels of conservatism can be chosen based on expected manufacturing quality. For instance, the most and least conservative of the three design guidelines differ by a factor of 3 for the most slender cylinder geometries, and the associated reduction in safety factor has profound implications for efficient structural design. This article is part of the theme issue 'Probing and dynamics of shock sensitive shells'.

A robust optimization model for tactical capacity planning in an outpatient setting.

Tactical capacity planning is a key element of planning and control decisions in healthcare settings, focusing on the medium-term allocation of a clinic's resources to appointments of different types. One of the most scarce resources in healthcare is physician time. Due to uncertainty in demand for appointments, it is difficult to provide an exact match between the planned physician availability and appointment requests. Our study uses cardinality-constrained robust optimization to develop tactical capacity plans which are robust against uncertainty, providing a feasible allocation of capacity for all realizations of demand to the extent allowed by the budget of uncertainty. The outpatient setting we consider sees first-visit patients and re-visit patients, and both patient types have access time targets. We experimentally evaluate our robust model and its practical implications under different levels of conservatism. We show that we can guarantee 100% feasibility of the robust tactical capacity plan while not being fully conservative, which will lead to the clinic saving money while being able to meet demand despite uncertainty. We also show how the robust model helps us to identify the critical time periods leading to worst case physician peak load, which could be valuable to decision-makers. Throughout the experiments, we find that the step of translating available data into an uncertainty set can influence the true conservatism of a solution.

Hybrid Model for Wind Turbine Main Bearing Fatigue with Uncertainty in Grease Observations


 
 
 Available historical field data shows that wind turbine main bearing failure can lead to major operation and maintenance costs due to unscheduled downtime. For legacy turbines, fa- tigue is one of the major failure modes and, to a degree, can be partially modeled with physics-based formulations. Unfor- tunately, existing bearing fatigue models can potentially be inaccurate due to lack of understanding of the lubricant degra- dation. One way to enhance these models is to track the grease damage along with the bearing fatigue damage. However, the need of grease degradation data can become an impedi- ment for such strategy. In this paper, we will demonstrate that it is possible to calibrate grease degradation models with cost-efficient periodic visual inspections. Knowing that such inspections introduce observation uncertainty to the model, we will use a hybrid physics-informed deep neural networks to quantify such uncertainties within our models. We built a hybrid model that fuses the physics-based understanding of the bearing fatigue failure with the ability of data-driven layers to compensate the missing physics, with respect to the grease degradation. The proposed hybrid model is also ca- pable of decoding uncertain visual grease inspections with a custom designed classifier. We illustrate the merits of the model with the support of case studies, where we test inspec- tion with different levels of conservatism to train the model and compare the predictions of these models on an artificial wind park. Results from the case studies indicate the success- ful prognostic performance of the trained with limited and noisy observations. While grease damage is predicted with 0.3% root mean square error as a result of baseline inspection campaign, bearing life is prediction is conservatively off only by months for aggressive turbines that have 10 years of life.
 
 

Smart home energy management using hybrid robust-stochastic optimization

This paper proposes a hybrid robust-stochastic optimization model for smart home energy management in day-ahead (DA) and real-time (RT) energy markets which the uncertainties of energy prices and PV generation are investigated in the proposed model. A flexible robust optimization approach (ROA) is employed to create a tractable equivalent of the problem and manages the uncertainty of DA market prices when the PV generation is assumed in the worst-case. The ROA conservatism level can be adjusted by a control parameter and solutions with different levels of conservatism are obtained. Also, the proposed optimization framework considers the RT energy market and takes into account the associated uncertainties using stochastic programming (SP). At this stage, probable scenarios are used to model the uncertain characteristics of PV generation and energy prices. Loads are also considered to be controllable, while the comfort of inhabitants is considered. Results analysis show the advantage of the proposed hybrid method which makes sure decision-maker about the profitability of energy management. In the most conservatism case, the summation of profits of DA and RT markets is about 2.5 $/day.

A Hybrid Meta-Heuristic for a Bi-Objective Stochastic Optimization of Urban Water Supply System

The restoration and remodeling of the urban water supply system are traditional challenges for water companies due to either aged existing water supply networks or lodging expansion. These challenges involve the uncertainties induced by their lengthy-planned prospects and the impossible exact prediction of forthcoming events. In this regard, correlations exacerbate unpredictable data and parameters and probably undermine taking effective decisions in this context. Therefore, the remodel and restoration decision of water supply systems must be made using approaches that can effectively deal with correlation uncertainties. The present study develops a bi-objective stochastic optimization model that can handle interrelated uncertain parameters in the water supply system remodeling and restoration issue. The proposed mathematical model is validated using the data of the Mashhad Plain water supply system as a real case study, followed by performing and comparing different levels of conservatism and reliability. As a complex optimization problem, an efficient algorithm is needed to solve the problem. To this end, a hybrid meta-heuristic algorithm, which is a combination of the Red Deer Algorithm (as a newly introduced nature-inspired heuristic) and Simulated Annealing (as a traditional local search algorithm), is proposed. Considering the advantages of these algorithms, it is possible to alleviate the disadvantages of current methods when solving large-scale networks. Finally, an extensive comparison and discussion are made and then the main findings with practical solutions are presented to significantly evaluate the proposed model and algorithm.

Accounting conservatism in complex companies

ABSTRACT This study seeks to investigate the influence of the complexity of companies on levels of accounting conservatism. The subject of analysis, accounting conservatism in complex companies, can be considered relevant because it analyzes conservative practices taking into account the organizational context of companies; something that is ignored in other studies that investigate the incentives or determinants of accounting conservatism, at least as far as firm complexity is concerned. The research presents statistical evidence that accounting conservatism varies positively with the information asymmetry caused by specific characteristics of complex environments. On the other hand, when companies present several complex characteristics together, then the trend is one of little adoption of conservatism. In addition, this research brings together evidence that aims to contribute to accounting science by analyzing complex companies and conservatism and not the opportunistic practices observed in previous studies. The sample refers to 110 publicly traded companies from 2010 to 2016. The data collection was carried out using company reports, such as reference forms, registration data, and explanatory notes, as well as the Economatica® database. The data analysis was performed using multiple linear regression and quantile regression. The evidence obtained in the research indicates that accounting conservatism varies according to the information asymmetry caused by complex environments, in which it can present a positive relationship in companies with few characteristics of complexity, or a negative relationship if the company has complexity in several characteristics at the same time. It throws light on the different levels of conservatism observed in companies, which can often be attributed to mechanisms of governance, organizational culture, and accounting standards, among other factors, which are results that may be biased if the company complexity factor is not considered.

Robust optimization for day-ahead market participation of smart-home aggregators

This paper proposes an optimization model to participate in day-ahead energy markets when PV generation, thermal and electro-chemical storage devices are aggregated at the residential level. The model includes uncertainty in energy prices, PV and load; and adjustable robust optimization is used to determine a tractable counterpart of the problem. By means of robust control parameters, solutions with different levels of conservatism can be found and analyzed. In addition, the presented model includes explicit representation of battery degradation by means of special ordered sets. This equivalent cycling aging calculation takes into account the non-linear relation between depth of discharge and total life cycles of the battery by piecewise linearization. Performance analysis shows the advantage of the proposed approach when compared to the deterministic solution in terms of average cost and risk. For the analyzed real-life test system, the robust formulation achieves cost reduction of up to 5.7% and standard deviation decreases as much as 36.4%.

How should the regulatory defaults be set?

Abstract How to choose defaults in risk-informed regulations depends on the conservatism implicated in regulatory defaults. Without a universal agreement on the approaches dealing with the conservatism of defaults, however, the desirability of conservatism in regulatory risk analyses has long been controversial. The opponent views it as needlessly costly and irrational, and the proponent as a form of protection against possible omissions or underestimation of risks. Moreover, the inherent ambiguity of risk makes it difficult to set suitable defaults in terms of risk. This paper, the extension of the previous work [1], focuses on the effects of different levels of conservatism implicated in regulatory defaults on the estimates of risk. According to the postulated behaviors of regulated parties and the diversity of interests of regulators, in particular, various measures for evaluating the effect of conservatism in defaults are developed and their properties are explored. In addition, a simple decision model for setting regulatory defaults is formulated, based on the understanding of the effect of conservatism implicated in them. It can help decision makers evaluate the levels of safety likely to result from their regulatory policies.

Accounting reforms and conservatism in earnings: Empirical evidence from listed Chinese companies

We examine the effects of the two major accounting reforms of 2001 and 2007 in China on conservatism in earnings using a variety of measures to ascertain the existence of conservatism and to gauge its degree. Our results provide evidence of different levels of conservatism in financial reporting in China during the period under investigation. We suggest that conservatism has generally existed in financial reporting in China since the 1998 accounting reform. However, the effects of the two accounting reforms on conservatism in earnings vary. Specifically, the 2001 accounting reforms significantly improved conservatism in earnings whereas the 2007 reforms reduced the extent of conservatism in earnings. We also note that conservatism in earnings rebounded following the 2007–09 global financial crisis. Furthermore, the 2001 accounting reforms have a greater positive impact on conservatism in earnings in regions with a lower level of legal protection for investors whereas the negative impact of the 2007 accounting reforms on conservatism in earnings is not affected by the level of legal protection for investors. These results suggest that accounting reforms that restrict managers’ abilities to conduct earnings management and improve conservatism in earnings serve as an important substitute mechanism for institutions of investor protection. Our findings provide useful insights into accounting conservatism and have important theoretical and practical implications for accounting regulators, investors, and researchers.

APROBA-Plus: A probabilistic tool to evaluate and express uncertainty in hazard characterization and exposure assessment of substances

To facilitate the application of probabilistic risk assessment, the WHO released the APROBA tool. This tool applies lognormal uncertainty distributions to the different aspects of the hazard characterization, resulting in a probabilistic health-based guidance value. The current paper describes an extension, APROBA-Plus, which combines the output from the probabilistic hazard characterization with the probabilistic exposure to rapidly characterize risk and its uncertainty. The uncertainty in exposure is graphically compared with the uncertainty in the target human dose, i.e. the dose that complies with the specified protection goals. APROBA-Plus is applied to several case studies, resulting in distinct outcomes and illustrating that APROBA-Plus could serve as a standard extension of routine risk assessments. By visualizing the uncertainties, APROBA-Plus provides a more transparent and informative outcome than the more usual deterministic approaches, so that risk managers can make better informed decisions. For example, APROBA-Plus can help in deciding whether risk-reducing measures are warranted or that a refined risk assessment would first be needed. If the latter, the tool can be used to prioritize possible refinements. APROBA-Plus may also be used to rank substances into different risk categories, based on potential health risks without being compromised by different levels of conservatism that may be associated with point estimates of risk.

Robust production scheduling in open-pit mining under uncertainty: a box counterpart approach

Open-Pit Production Scheduling (OPPS) problem focuses on determining a block sequencing and scheduling to maximize Net Present Value (NPV) of the venture under constraints. The scheduling model is critically sensitive to the economic value volatility of block, block weight, and operational capacity. In order to deal with the OPPS uncertainties, various approaches can be recommended. Robust optimization is one of the most applicable methods in this area used in this study. Robust optimization based on the box counterpart formulation is applied to deal with the OPPS problem. To have a comparison between the solutions of the box counterpart optimization model and the deterministic model, a Two-Dimensional (2D) numerical study of a hypothetical open-pit mine is conducted followed by additional computations on the actual large-scale instances (Marvin orebody). This investigation shows that the different features of the robust planning under uncertainty can be scheduled. Also the price of robustness is obtained in different levels of conservatism.

Assessment of epistemic uncertainties in the shear strength of slender reinforced concrete beams

Selection of an appropriate model for shear capacity of reinforced concrete (RC) slender beams poses a number of challenges. First, different models with different levels of conservatism have been proposed in an attempt to describe shear resistance. Second, according to Reineck et al. (2014), code provisions for shear capacity of RC beams with shear reinforcement have been primarily derived from test data with respect to the required amount of shear reinforcement and the calculation of maximum shear capacity. Third, current models have been developed based on databases presenting two major drawbacks: (i) most data points are crowded in the small size range, and (ii) the means of the subsidiary influencing parameters are very different within different intervals of beam size (or beam depth). In this study, a filtered database is used in such a way to circumvent the drawbacks mentioned above. A random variable “model error”, i.e. ratio experimental to predicted shear strength, is associated to each of the shear models analyzed in this work (NBR 6118, ACI 318, EUROCODE 2, and CSA A.23.3). It was observed that in some cases, most notably for the effective depth, a trend exists for a decrease in the “model error” as the effective depth increases. Considering the limitations of the four analyzed models, a nonlinear regression model was proposed. The database presented by Reineck et al. (2014) was used in the assessment of the effectiveness and accuracy of the proposed regression model. No trend was found associated to the most significant variables in the shear strength prediction, i.e. a uniform level of conservatism is attained throughout the range of these variables. The regression model proposed herein and the attendant statistics of the model error (mean, coefficient of variation and type of distribution) can be easily used in a reliability analysis procedure to assess safety levels implicit in different design procedures.

Level and length of cyclic solar activity during the Maunder minimum as deduced from the active-day statistics

The Maunder minimum (MM) of greatly reduced solar activity took place in 1645-1715, but the exact level of sunspot activity is uncertain as based, to a large extent, on historical generic statements of the absence of spots on the Sun. Here we aim, using a conservative approach, to assess the level and length of solar cycle during the Maunder minimum, on the basis of direct historical records by astronomers of that time. A database of the active and inactive days (days with and without recorded sunspots on the solar disc respectively) is constructed for three models of different levels of conservatism (loose ML, optimum MO and strict MS models) regarding generic no-spot records. We have used the active day fraction to estimate the group sunspot number during the MM. A clear cyclic variability is found throughout the MM with peaks at around 1655--1657, 1675, 1684 and 1705, and possibly 1666, with the active day fraction not exceeding 0.2, 0.3 or 0.4 during the core MM, for the three models. Estimated sunspot numbers are found very low in accordance with a grand minimum of solar activity. We have found, for the core MM (1650-1700), that: (1) A large fraction of no-spot records, corresponding to the solar meridian observations, may be unreliable in the conventional database. (2) The active day fraction remained low (below 0.3-0.4) throughout the MM, indicating the low level of sunspot activity. (3) The solar cycle appears clearly during the core MM. (4) The length of the solar cycle during the core MM appears $9\pm 1$ years, but there is an uncertainty in that. (5) The magnitude of the sunspot cycle during MM is assessed to be below 5-10 in sunspot numbers; A hypothesis of the high solar cycles during the MM is not confirmed.

Measuring technical efficiency of potato production in Iran using robust data envelopment analysis

A non-parametric method of data envelopment analysis (DEA) was applied to analyze the technical and scale efficiency of potato production in 23 Iranian provinces. In many real applications, inputs and outputs may be imprecise. In the present study, a robust DEA (RDEA) optimization framework was used to concentrate on DEA with uncertain data. The method was based on six inputs (human labor rent, land rent, diesel and machinery rent, irrigation water cost, fertilizer cost, pesticide cost) and the single output of potato gross return. The proposed DEA for 23 Iranian potato-producing provinces reveals that the average technical efficiency is 90% and scale efficiency is 97%. This suggests that inefficient provinces can potentially reduce their overall costs for potato production. A Monte Carlo simulation was used to compute the conformity of the rankings from the RDEA model with reality to illustrate the importance of varying the level of efficiency for different levels of conservatism.

Budgeting Fuel Consumption of Container Ship over Round-Trip Voyage through Robust Optimization

A proposed practical fuel budget problem aims to determine a group of bunker fuel budget values for a liner container ship over a round-trip voyage under uncertainties caused by severe weather conditions. According to research collaboration with a global container shipping line in Singapore, the proposed problem holds a kernel position in the ship fuel efficiency management programs advocated by container shipping lines because of the downward pressure of soaring bunker prices. The synergetic influence of sailing speed and weather conditions on ship fuel consumption rate was considered when the bunker fuel budget of a ship over a round-trip voyage was estimated. To address the adverse random perturbation of fuel consumption rate under severe weather conditions, state-of-the-art robust optimization techniques were employed, and a robust optimization model for the fuel budget problem was developed. The developed model can be dualized into a mixed-integer linear programming model that may be solved by commercial optimization solvers. However, algorithmic findings in the field of robust optimization provided a polynomial time solution algorithm, and it was retrofitted to accommodate the proposed ship fuel budget problem. The case study of an Asia–Europe service demonstrates the computational performance of the proposed solution algorithm and the competence of the proposed robust optimization model to produce fuel budget values at different levels of conservatism possessed by the fuel efficiency specialists in container shipping lines.

Stochastic stability of Positive Markov Jump Linear Systems

This paper investigates on the stability properties of Positive Markov Jump Linear Systems (PMJLS’s), i.e. Markov Jump Linear Systems with nonnegative state variables. Specific features of these systems are highlighted. In particular, a new notion of stability (Exponential Mean stability) is introduced and is shown to be equivalent to the standard notion of 1-moment stability. Moreover, various sufficient conditions for Exponential Almost-Sure stability are worked out, with different levels of conservatism. The implications among the different stability notions are discussed. It is remarkable that, thanks to the positivity assumption, some conditions can be checked by solving Linear Programming feasibility problems.

Book Reviews

Book Reviews

Target Cleanup Levels at the Site of a Former Manufactured Gas Plant in Northern Italy: Deterministic versus Probabilistic Results

A quantitative analysis of allowable soil concentrations using deterministic and probabilistic risk analysis methods was carried out for a large and heavily contaminated industrial site where remediation costs to meet soil standards (not risk-based) issued by the regulatory agency were higher than the commercial value of the site. Deterministic cleanup targets, based on a risk-based corrective action procedure, allow a 5-fold reduction in the volume of soil to be decontaminated. The site-specific, probabilistic analysis shows that the deterministic cleanup standards for volatile organic compounds were lower than those required to meet the probabilistic criteria but were higher, and thus less conservative, for polycyclic aromatic hydrocarbons and inorganic substances. The probabilistic methods used show that deterministic standards may hide significantly different levels of conservatism in relation to the uncertainty and variability present in each exposure parameter. The expediency of probabilistic calculation to avoid over-remediation efforts is not certain as probabilistic results may be more stringent than deterministic ones; therefore, remediation costs are related not only to the allowable concentrations of single species but also to the mix of contaminants found on a specific site.