The Affecting Factors of Audit Quality with Earnings Surprise Benchmark Approach as a Measure of Audit Quality

This research examines whether abnormal audit fee, client importance, public accounting firm industry (PAF) specialization, public accounting firm (PAF) reputation, audit delay may affect the audit quality of manufacturing companies. This research used a quantitative method as a basis for assessing audit quality using the earnings surprise benchmark method, which emphasizes the profits generated by the company. This research used 350 data panel samples from manufacturing companies that have been listed on the Indonesia Stock Exchange (IDX) throughout 2013-2019. Sampling using non-probability with purposive sampling technique, and to analyze the data, the researcher used logistic regression because the dependent variable in this research only consisted of two values. This research shows that abnormal audit fees affect negatively significant to audit quality, while client importance and public accounting firm industry specialization affects positively significant to the audit. However, public accounting firm reputation does not have a positive effect on audit quality, and audit delay does not negatively affect significantly on audit quality. This research is the first time to examine abnormal audit fees on audit quality using earning surprise benchmark calculation method. Results from this research are expected to be beneficial for policy determination and audit standard development by related regulations and research development on audit quality.

PWR MOX/UO2 Transient Benchmark Calculation Using Monte Carlo Serpent 2 Code and Open Nodal Core Simulator ADPRES

This paper presents static and transient solutions for the PWR MOX/UO2 transient benchmark by Serpent 2 Monte Carlo code and open nodal core simulator called ADPRES. The presences of MOX fuels and burn-up variation in the benchmark’s reactor core pose challenges for reactor simulators due to severe flux gradient across fuel assemblies. In this work, the two-step method was used, in which the assembly level two-group constants were generated from single assembly calculations with zero net current boundary conditions using Serpent 2 Monte Carlo code, and later the core calculation was performed using ADPRES open nodal core simulator. Two types of diffusion coefficients were generated: the conventional B1 leakage corrected and Cumulative Migration Method (CMM). Finally, the solutions of Serpent 2/ADPRESS, including multiplication factor, power distribution, control rod worth, and critical boron concentration using both diffusion coefficients were compared against solutions from heterogeneous Serpent 2 calculations where the fuel and cladding are explicitly modeled. The reactor power during transients were also compared qualitatively against other nodal core simulators. The results showed that Serpent 2/ADPRES were able to predict the heterogeneous Monte Carlo solutions very well with reasonable differences. The transient solutions were also quite accurate compared to other nodal core simulators. As for the diffusion coefficients comparison, it was found that the CMM diffusion coefficient provide more accurate solutions for the benchmark compared to the B1 leakage corrected diffusion coefficients.

Quantitative analysis of optimum corrective fuel tax for road vehicles in Bangladesh: achieving the greenhouse gas reduction goal

This study estimates optimum corrective fuel taxes for Bangladesh and correlates them with climate change policy. First, we use the European road transport emission model (COPERT IV) to precisely estimate the externalities. Second, using the same model, we also estimate the reduction in greenhouse gas emissions caused by the fuel tax. Finally, we develop a correlation between the fuel tax rate and emissions reduction. Our benchmark calculation of the optimum corrective tax is US$0.94 per gallon for gasoline and US$1.46 per gallon for diesel (in 2016 prices). We find that congestion and accident externalities are the two main fuel tax components for Bangladesh. We also find that the net social welfare gain per year is US$302.11 million and the net revenue gain per year is 3.59% of GDP. The corrective diesel tax reduces fuel consumption by 18.10% and increases fuel efficiency by 12.53%. In the benchmark case, corrective fuel taxes reduce GHG emissions by 5.77%. With the combination of the existing gasoline tax and a diesel tax of US$1.20 per gallon, the country’s greenhouse gas reduction goal can be achieved. Policymakers can use fuel taxes to support climate change policy.

Fatigue Benchmark Comparison Effort Between Code_Aster and CNNC/NPIC Software: Part 1

Fatigue is identified as a significant degradation mode that affects nuclear power plants world-wide. Several international codes and standards (ASME, RCC-M, JSME, etc...) offer rules to predict its damaging effect on the locations of the various components of an NPP. These rules, which ensure conservatism and safe operation, have grown in complexity over the years because they have integrated R&D results showing aggravating effects that were not included in the original analyses (such as Environmental Assisted Fatigue[1][2]) but also because an economically viable design of components has required optimization and refinement of mechanical assessment methods. CNNC/NPIC has been following carefully the recent evolutions in the fatigue rules and has today finalized an in-house software enabling the evaluation of fatigue per ASME and RCC-M rules, with integration of environmental effects. On the other hand, EDF has been developing since 1989 its own in-house FEA code baptizedCode_Aster that is included in the Salome-Meca mechanical package. Salome-Meca is open-access and can be used freely by international users. Within Code_Aster, the fatigue postprocessor offers a span of criteria (Dang Van, Stress Intensity, etc...) to pick and choose from and even offers the possibility to make up owns one fatigue criteria. It also offers the possibility to post-process fatigue according to the RCC-M rules (POST_RCCM operator). It has been recently updated to perform industrial calculations integrating environmental fatigue[2][3]. Both entities have come to agree that validating a fatigue computer code is not an easy task. On the one hand, the full validation using hand calculations would be a highly tedious effort, given the technicality and the multiple choices to make along the various steps of the fatigue analysis. On the other hand, there are no experiments today which enable to directly lead a benchmark calculation to validate fatigue numerical results. In consequence, an accepted way of validating a code is to perform a benchmark analysis against another industrial fatigue code. CNNC/NPIC and EDF R&D China have therefore launched an effort to benchmark their respective codes, with the final objective of progressing together towards safe structural assessment practical methods for their power plants components.