additional references

paper.bib

@@ -69,7 +69,7 @@ @article{conde2017implicit
 
 
 @inproceedings{2018_wso,
-	Author = {Ketcheson, David and Seibold, Benjamin and Shirokoff, David and Zhou, Dong},
+	Author = {Ketcheson, David I. and Seibold, Benjamin and Shirokoff, David and Zhou, Dong},
 	Booktitle = {Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2018},
 	Editor = {Sherwin, Spencer et. al.w},
 	Title = {DIRK Schemes with High Weak Stage Order},
@@ -209,3 +209,25 @@ @article{conde2018embedded
   journal={arXiv preprint arXiv:1806.08693},
   year={2018}
 }
+
+@article{vermeire2019optimal,
+  title={Optimal {R}unge--{K}utta schemes for pseudo time-stepping with
+         high-order unstructured methods},
+  author={Vermeire, Brian C and Loppi, Niki A and Vincent, Peter E},
+  journal={Journal of Computational Physics},
+  volume={383},
+  pages={55--71},
+  year={2019},
+  publisher={Elsevier},
+  doi={10.1016/j.jcp.2019.01.003}
+}
+
+@article{vermeire2020optimal,
+  title={Optimal embedded pair {R}unge--{K}utta schemes for pseudo-time stepping},
+  author={Vermeire, Brian C and Loppi, Niki A and Vincent, Peter E},
+  journal={Journal of Computational Physics},
+  pages={109499},
+  year={2020},
+  publisher={Elsevier},
+  doi={10.1016/j.jcp.2020.109499}
+}

paper.md

@@ -44,7 +44,7 @@ The original (and still primary) focus of the package is on the design of
 Runge-Kutta methods, but some routines for designing other classes of methods
 are also included.
 
-# Statement of need 
+# Statement of need
 
 Over the last several decades, a great deal of work has gone into the design
 of numerical ODE solvers.  Initially this work was aimed at developing general
@@ -129,14 +129,14 @@ enabling its efficient solution for methods with many steps.
 
 # Related research and software
 
-`RK-Opt` development has proceeded in close connection to the `NodePy` package.
-Whereas `RK-Opt` is focused on the design of numerical methods, `NodePy` is focused 
+`RK-Opt` development has proceeded in close connection to the `NodePy` package (https://github.com/ketch/NodePy).
+Whereas `RK-Opt` is focused on the design of numerical methods, `NodePy` is focused
 more on their analysis.  A common workflow involves generating new methods with
 `RK-Opt` and then studying their properties in more detail using `NodePy`.
 
 Some of the research projects that have made use of `RK-Opt` include development of:
 
- - SSP Runge-Kutta methods 
+ - SSP Runge-Kutta methods
    [@2008_explicit_ssp;@2009_implicit_ssp;@gottlieb2015optimal]
  - SSP linear multistep methods [@2009_monotonicity]
  - SSP general linear methods [@2011_tsrk;@2017_msrk]
@@ -145,10 +145,11 @@ Some of the research projects that have made use of `RK-Opt` include development
  - Optimal Runge-Kutta stability polynomials [@2012_optimal_stability_polynomials]
  - Additive and downwind SSP Runge-Kutta methods [@2011_dwssp;@2018_perturbations]
  - Optimal Runge-Kutta methods for specific PDE semi-discretizations [@parsani-eccomas;@Parsani_finnish;@2013_sd_erk;@2014_ssp_rkdg]
+ - Optimal Runge-Kutta methods for pseudo-time stepping [@vermeire2019optimal;@vermeire2020optimal]
  - Embedded pairs for Runge-Kutta methods [@conde2018embedded]
  - Runge-Kutta methods with high weak stage order [@2018_wso]
  - SSP multistage, multiderivative methods [@christlieb2016explicit;@grant2019strong;@reynoso2017strong]
- 
+
 As can be seen from this list, applications have mostly stemmed from the
 work of the main developer's research group, but have since expanded
 beyond that.