Example of Frontiers of Structural and Civil Engineering format
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Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format Example of Frontiers of Structural and Civil Engineering format
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open access Open Access

Frontiers of Structural and Civil Engineering — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Architecture #18 of 138 up up by 1 rank
Civil and Structural Engineering #130 of 318 up up by 1 rank
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 310 Published Papers | 942 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 13/06/2020
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Insights
General info
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FAQ

Related Journals

open access Open Access
recommended Recommended

Emerald Publishing

Quality:  
High
CiteRatio: 3.6
SJR: 0.455
SNIP: 1.13
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Springer

Quality:  
Good
CiteRatio: 1.1
SJR: 0.205
SNIP: 0.636
open access Open Access
recommended Recommended

Taylor and Francis

Quality:  
High
CiteRatio: 5.9
SJR: 0.972
SNIP: 1.349

Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

A measure of average citations received per peer-reviewed paper published in the journal.

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

3.0

25% from 2019

CiteRatio for Frontiers of Structural and Civil Engineering from 2016 - 2020
Year Value
2020 3.0
2019 2.4
2018 2.0
2017 1.8
2016 1.4
graph view Graph view
table view Table view

0.594

22% from 2019

SJR for Frontiers of Structural and Civil Engineering from 2016 - 2020
Year Value
2020 0.594
2019 0.486
2018 0.401
2017 0.616
2016 0.467
graph view Graph view
table view Table view

0.965

5% from 2019

SNIP for Frontiers of Structural and Civil Engineering from 2016 - 2020
Year Value
2020 0.965
2019 0.923
2018 0.682
2017 0.845
2016 0.685
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has increased by 25% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has increased by 22% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 5% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Frontiers of Structural and Civil Engineering

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Springer

Frontiers of Structural and Civil Engineering

Approved by publishing and review experts on SciSpace, this template is built as per for Frontiers of Structural and Civil Engineering formatting guidelines as mentioned in Springer author instructions. The current version was created on 13 Jun 2020 and has been used by 343 authors to write and format their manuscripts to this journal.

Engineering

i
Last updated on
13 Jun 2020
i
ISSN
2095-2430
i
Impact Factor
Medium - 0.802
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
SPBASIC
i
Citation Type
Author Year
(Blonder et al, 1982)
i
Bibliography Example
Beenakker CWJ (2006) Specular andreev reflection in graphene. Phys Rev Lett 97(6):067,007, URL 10.1103/PhysRevLett.97.067007

Top papers written in this journal

Journal Article DOI: 10.1007/S11709-016-0363-9
Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressive strength of concrete
Faezehossadat Khademi1, Mahmoud Akbari2, Sayed Mohammadmehdi Jamal, Mehdi Nikoo3

Abstract:

Evaluating the in situ concrete compressive strength by means of cores cut from hardened concrete is acknowledged as the most ordinary method, however, it is very difficult to predict the compressive strength of concrete since it is affected by many factors such as different mix designs, methods of mixing, curing conditions, ... Evaluating the in situ concrete compressive strength by means of cores cut from hardened concrete is acknowledged as the most ordinary method, however, it is very difficult to predict the compressive strength of concrete since it is affected by many factors such as different mix designs, methods of mixing, curing conditions, compaction, etc. In this paper, considering the experimental results, three different models of multiple linear regression model (MLR), artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS) are established, trained, and tested within the Matlab programming environment for predicting the 28 days compressive strength of concrete with 173 different mix designs. Finally, these three models are compared with each other and resulted in the fact that ANN and ANFIS models enables us to reliably evaluate the compressive strength of concrete with different mix designs, however, multiple linear regression model is not feasible enough in this area because of nonlinear relationship between the concrete mix parameters. Finally, the sensitivity analysis (SA) for two different sets of parameters on the concrete compressive strength prediction are carried out. read more read less

Topics:

Compressive strength (59%)59% related to the paper, Adaptive neuro fuzzy inference system (54%)54% related to the paper
185 Citations
Journal Article DOI: 10.1007/S11709-017-0430-X
A critical review of preparation design and workability measurement of concrete material for largescale 3D printing
Guowei Ma1, Guowei Ma2, Li Wang3

Abstract:

In recent few years, significant improvement has been made in developing largescale 3D printers to accommodate the need of industrial-scale 3D printing. It is of great feasibility to construct structural components and buildings by means of 3D concrete printing. The major issues of this innovative technique focus on the prepa... In recent few years, significant improvement has been made in developing largescale 3D printers to accommodate the need of industrial-scale 3D printing. It is of great feasibility to construct structural components and buildings by means of 3D concrete printing. The major issues of this innovative technique focus on the preparation and optimization of concrete materials which possess favourable printable properties as well as the measurement and evaluation methods of their workability. This paper firstly introduces three largescale 3D printing systems that have been successfully applied in construction industry. It then summarizes the commonly used raw materials in concrete manufacturing. Critical factors that should be particularly controlled in material preparation are specified. Easy-extrusive, easy-flowing, well-buildable, proper setting time and low shrinkage are significant for concrete mixture to meet the critical requirements of a freeform construction process. Thereafter, measuring methods that can be employed to assess the fresh and hardened properties of concrete at early stages are suggested. Finally, a few of evaluation methods are presented which may offer certain assistance for optimizing material preparation. The objective of this work is to review current design methodologies and experimental measurement and evaluation methods for 3D printable concrete materials and promote its responsible use with largescale 3D printing technology. read more read less

Topics:

Properties of concrete (55%)55% related to the paper
135 Citations
Journal Article DOI: 10.1007/S11709-012-0141-2
Modeling of alkali-silica reaction in concrete:a review
Jianwen Pan1, Jianwen Pan2, Yuntian Feng1, Jin-Ting Wang2, Qicheng Sun2, Chuhan Zhang2, David R. Owen1

Abstract:

This paper presents a comprehensive review of modeling of alkali-silica reaction (ASR) in concrete. Such modeling is essential for investigating the chemical expansion mechanism and the subsequent influence on the mechanical aspects of the material. The concept of ASR and the mechanism of expansion are first outlined, and the... This paper presents a comprehensive review of modeling of alkali-silica reaction (ASR) in concrete. Such modeling is essential for investigating the chemical expansion mechanism and the subsequent influence on the mechanical aspects of the material. The concept of ASR and the mechanism of expansion are first outlined, and the state-of-the-art of modeling for ASR, the focus of the paper, is then presented in detail. The modeling includes theoretical approaches, meso- and macroscopic models for ASR analysis. The theoretical approaches dealt with the chemical reaction mechanism and were used for predicting pessimum size of aggregate. Mesoscopic models have attempted to explain the mechanism of mechanical deterioration of ASR-affected concrete at material scale. The macroscopic models, chemomechanical coupling models, have been generally developed by combining the chemical reaction kinetics with linear or nonlinear mechanical constitutive, and were applied to reproduce and predict the long-term behavior of structures suffering from ASR. Finally, a conclusion and discussion of the modeling are given. read more read less
81 Citations
Journal Article DOI: 10.1007/S11709-019-0561-3
Prediction of shield tunneling-induced ground settlement using machine learning techniques
Renpeng Chen1, Pin Zhang1, Huaina Wu1, Zhi-Teng Wang1, Zhi-Quan Zhong

Abstract:

Predicting the tunneling-induced maximum ground surface settlement is a complex problem since the settlement depends on plenty of intrinsic and extrinsic factors. This study investigates the efficiency and feasibility of six machine learning (ML) algorithms, namely, back-propagation neural network, wavelet neural network, gen... Predicting the tunneling-induced maximum ground surface settlement is a complex problem since the settlement depends on plenty of intrinsic and extrinsic factors. This study investigates the efficiency and feasibility of six machine learning (ML) algorithms, namely, back-propagation neural network, wavelet neural network, general regression neural network (GRNN), extreme learning machine, support vector machine and random forest (RF), to predict tunneling-induced settlement. Field data sets including geological conditions, shield operational parameters, and tunnel geometry collected from four sections of tunnel with a total of 3.93 km are used to build models. Three indicators, mean absolute error, root mean absolute error, and coefficient of determination the (R2) are used to demonstrate the performance of each computational model. The results indicated that ML algorithms have great potential to predict tunneling-induced settlement, compared with the traditional multivariate linear regression method. GRNN and RF algorithms show the best performance among six ML algorithms, which accurately recognize the evolution of tunneling-induced settlement. The correlation between the input variables and settlement is also investigated by Pearson correlation coefficient. read more read less

Topics:

Settlement (structural) (60%)60% related to the paper, Extreme learning machine (56%)56% related to the paper, Artificial neural network (54%)54% related to the paper, Support vector machine (52%)52% related to the paper, Pearson product-moment correlation coefficient (51%)51% related to the paper
78 Citations
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Frequently asked questions

1. Can I write Frontiers of Structural and Civil Engineering in LaTeX?

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2. Do you follow the Frontiers of Structural and Civil Engineering guidelines?

Yes, the template is compliant with the Frontiers of Structural and Civil Engineering guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Frontiers of Structural and Civil Engineering?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Frontiers of Structural and Civil Engineering citation style.

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Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Frontiers of Structural and Civil Engineering.

5. Can I use a manuscript in Frontiers of Structural and Civil Engineering that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Frontiers of Structural and Civil Engineering that you can download at the end.

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It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Frontiers of Structural and Civil Engineering.

7. Where can I find the template for the Frontiers of Structural and Civil Engineering?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Frontiers of Structural and Civil Engineering's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

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Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

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SciSpace's Frontiers of Structural and Civil Engineering is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

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After writing your paper autoformatting in Frontiers of Structural and Civil Engineering, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Frontiers of Structural and Civil Engineering's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Frontiers of Structural and Civil Engineering?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Frontiers of Structural and Civil Engineering. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Frontiers of Structural and Civil Engineering?

The 5 most common citation types in order of usage for Frontiers of Structural and Civil Engineering are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Frontiers of Structural and Civil Engineering?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Frontiers of Structural and Civil Engineering's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Frontiers of Structural and Civil Engineering in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Frontiers of Structural and Civil Engineering Endnote style according to Elsevier guidelines.

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